[{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","related_material":{"link":[{"url":"https://github.com/IST-DASLab/MicroAdam","relation":"software"}]},"year":"2024","corr_author":"1","OA_type":"green","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2405.15593"}],"acknowledgement":"The authors thank Razvan Pascanu, Mahdi Nikdan and Soroush Tabesh for their valuable feedback, the IT department from Institute of Science and Technology Austria for the hardware support and Weights and Biases for the infrastructure to track all our experiments. Mher Safaryan has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 101034413.","scopus_import":"1","_id":"19510","author":[{"first_name":"Ionut-Vlad","id":"449f7a18-f128-11eb-9611-9b430c0c6333","last_name":"Modoranu","full_name":"Modoranu, Ionut-Vlad"},{"id":"dd546b39-0804-11ed-9c55-ef075c39778d","last_name":"Safaryan","full_name":"Safaryan, Mher","first_name":"Mher"},{"first_name":"Grigory","last_name":"Malinovsky","full_name":"Malinovsky, Grigory"},{"first_name":"Eldar","full_name":"Kurtic, Eldar","id":"47beb3a5-07b5-11eb-9b87-b108ec578218","last_name":"Kurtic"},{"first_name":"Thomas","full_name":"Robert, Thomas","id":"de632733-1457-11f0-ae22-b5914b8c1c41","last_name":"Robert"},{"first_name":"Peter","last_name":"Richtárik","full_name":"Richtárik, Peter"},{"full_name":"Alistarh, Dan-Adrian","last_name":"Alistarh","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-3650-940X","first_name":"Dan-Adrian"}],"date_created":"2025-04-06T22:01:32Z","department":[{"_id":"DaAl"}],"publication_status":"published","status":"public","publication":"38th Conference on Neural Information Processing Systems","oa_version":"Preprint","acknowledged_ssus":[{"_id":"CampIT"}],"date_updated":"2025-05-14T11:32:52Z","alternative_title":["Advances in Neural Information Processing Systems"],"day":"20","date_published":"2024-12-20T00:00:00Z","article_processing_charge":"No","title":"MICROADAM: Accurate adaptive optimization with low space overhead and provable convergence","ec_funded":1,"abstract":[{"text":"We propose a new variant of the Adam optimizer [Kingma and Ba, 2014] called\r\nMICROADAM that specifically minimizes memory overheads, while maintaining\r\ntheoretical convergence guarantees. We achieve this by compressing the gradient\r\ninformation before it is fed into the optimizer state, thereby reducing its memory\r\nfootprint significantly. We control the resulting compression error via a novel\r\ninstance of the classical error feedback mechanism from distributed optimization [Seide et al., 2014, Alistarh et al., 2018, Karimireddy et al., 2019] in which\r\nthe error correction information is itself compressed to allow for practical memory\r\ngains. We prove that the resulting approach maintains theoretical convergence\r\nguarantees competitive to those of AMSGrad, while providing good practical performance. Specifically, we show that MICROADAM can be implemented efficiently\r\non GPUs: on both million-scale (BERT) and billion-scale (LLaMA) models, MICROADAM provides practical convergence competitive to that of the uncompressed\r\nAdam baseline, with lower memory usage and similar running time. Our code is\r\navailable at https://github.com/IST-DASLab/MicroAdam.","lang":"eng"}],"arxiv":1,"citation":{"ama":"Modoranu I-V, Safaryan M, Malinovsky G, et al. MICROADAM: Accurate adaptive optimization with low space overhead and provable convergence. In: <i>38th Conference on Neural Information Processing Systems</i>. Vol 37. Neural Information Processing Systems Foundation; 2024.","apa":"Modoranu, I.-V., Safaryan, M., Malinovsky, G., Kurtic, E., Robert, T., Richtárik, P., &#38; Alistarh, D.-A. (2024). MICROADAM: Accurate adaptive optimization with low space overhead and provable convergence. In <i>38th Conference on Neural Information Processing Systems</i> (Vol. 37). Neural Information Processing Systems Foundation.","chicago":"Modoranu, Ionut-Vlad, Mher Safaryan, Grigory Malinovsky, Eldar Kurtic, Thomas Robert, Peter Richtárik, and Dan-Adrian Alistarh. “MICROADAM: Accurate Adaptive Optimization with Low Space Overhead and Provable Convergence.” In <i>38th Conference on Neural Information Processing Systems</i>, Vol. 37. Neural Information Processing Systems Foundation, 2024.","ista":"Modoranu I-V, Safaryan M, Malinovsky G, Kurtic E, Robert T, Richtárik P, Alistarh D-A. 2024. MICROADAM: Accurate adaptive optimization with low space overhead and provable convergence. 38th Conference on Neural Information Processing Systems. , Advances in Neural Information Processing Systems, vol. 37.","ieee":"I.-V. Modoranu <i>et al.</i>, “MICROADAM: Accurate adaptive optimization with low space overhead and provable convergence,” in <i>38th Conference on Neural Information Processing Systems</i>, 2024, vol. 37.","short":"I.-V. Modoranu, M. Safaryan, G. Malinovsky, E. Kurtic, T. Robert, P. Richtárik, D.-A. Alistarh, in:, 38th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2024.","mla":"Modoranu, Ionut-Vlad, et al. “MICROADAM: Accurate Adaptive Optimization with Low Space Overhead and Provable Convergence.” <i>38th Conference on Neural Information Processing Systems</i>, vol. 37, Neural Information Processing Systems Foundation, 2024."},"project":[{"_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c","call_identifier":"H2020","grant_number":"101034413","name":"IST-BRIDGE: International postdoctoral program"}],"oa":1,"volume":37,"publisher":"Neural Information Processing Systems Foundation","publication_identifier":{"issn":["1049-5258"]},"intvolume":"        37","OA_place":"repository","quality_controlled":"1","month":"12","type":"conference","external_id":{"arxiv":["2405.15593"]}},{"title":"QuaRot: Outlier-free 4-bit inference in rotated LLMs","arxiv":1,"abstract":[{"lang":"eng","text":"We introduce QuaRot, a new Quantization scheme based on Rotations, which is able to quantize LLMs end-to-end, including all weights, activations, and KV cache in 4 bits. QuaRot rotates LLMs in a way that removes outliers from the hidden state without changing the output, making quantization easier. This computational invariance is applied to the hidden state (residual) of the LLM, as well as to the activations of the feed-forward components, aspects of the attention mechanism, and to the KV cache. The result is a quantized model where all matrix multiplications are performed in 4 bits, without any channels identified for retention in higher precision. Our 4-bit quantized LLAMA2-70B model has losses of at most 0.47 WikiText-2 perplexity and retains 99% of the zero-shot performance. We also show that QuaRot can provide lossless 6 and 8 bit LLAMA-2 models without any calibration data using round-to-nearest quantization. Code is available at github.com/spcl/QuaRot."}],"status":"public","publication":"38th Conference on Neural Information Processing Systems","publication_status":"published","article_processing_charge":"No","date_published":"2024-12-20T00:00:00Z","date_updated":"2025-05-14T11:33:12Z","day":"20","alternative_title":["Advances in Neural Information Processing Systems"],"oa_version":"Preprint","conference":{"location":"Vancouver, Canada","name":"NeurIPS: Neural Information Processing Systems","end_date":"2024-12-15","start_date":"2024-12-09"},"intvolume":"        37","OA_place":"repository","publication_identifier":{"issn":["1049-5258"]},"volume":37,"publisher":"Neural Information Processing Systems Foundation","oa":1,"type":"conference","month":"12","external_id":{"arxiv":["2404.00456"]},"quality_controlled":"1","citation":{"apa":"Ashkboos, S., Mohtashami, A., Croci, M. L., Li, B., Cameron, P., Jaggi, M., … Hensman, J. (2024). QuaRot: Outlier-free 4-bit inference in rotated LLMs. In <i>38th Conference on Neural Information Processing Systems</i> (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.","ama":"Ashkboos S, Mohtashami A, Croci ML, et al. QuaRot: Outlier-free 4-bit inference in rotated LLMs. In: <i>38th Conference on Neural Information Processing Systems</i>. Vol 37. Neural Information Processing Systems Foundation; 2024.","short":"S. Ashkboos, A. Mohtashami, M.L. Croci, B. Li, P. Cameron, M. Jaggi, D.-A. Alistarh, T. Hoefler, J. Hensman, in:, 38th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2024.","mla":"Ashkboos, Saleh, et al. “QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs.” <i>38th Conference on Neural Information Processing Systems</i>, vol. 37, Neural Information Processing Systems Foundation, 2024.","ista":"Ashkboos S, Mohtashami A, Croci ML, Li B, Cameron P, Jaggi M, Alistarh D-A, Hoefler T, Hensman J. 2024. QuaRot: Outlier-free 4-bit inference in rotated LLMs. 38th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 37.","chicago":"Ashkboos, Saleh, Amirkeivan Mohtashami, Maximilian L. Croci, Bo Li, Pashmina Cameron, Martin Jaggi, Dan-Adrian Alistarh, Torsten Hoefler, and James Hensman. “QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs.” In <i>38th Conference on Neural Information Processing Systems</i>, Vol. 37. Neural Information Processing Systems Foundation, 2024.","ieee":"S. Ashkboos <i>et al.</i>, “QuaRot: Outlier-free 4-bit inference in rotated LLMs,” in <i>38th Conference on Neural Information Processing Systems</i>, Vancouver, Canada, 2024, vol. 37."},"OA_type":"green","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2404.00456","open_access":"1"}],"year":"2024","related_material":{"link":[{"url":"https://github.com/spcl/QuaRot","relation":"software"}]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","department":[{"_id":"DaAl"}],"date_created":"2025-04-06T22:01:32Z","author":[{"full_name":"Ashkboos, Saleh","last_name":"Ashkboos","first_name":"Saleh"},{"full_name":"Mohtashami, Amirkeivan","last_name":"Mohtashami","first_name":"Amirkeivan"},{"first_name":"Maximilian L.","full_name":"Croci, Maximilian L.","last_name":"Croci"},{"full_name":"Li, Bo","last_name":"Li","first_name":"Bo"},{"first_name":"Pashmina","full_name":"Cameron, Pashmina","last_name":"Cameron"},{"first_name":"Martin","full_name":"Jaggi, Martin","last_name":"Jaggi"},{"id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","last_name":"Alistarh","full_name":"Alistarh, Dan-Adrian","first_name":"Dan-Adrian","orcid":"0000-0003-3650-940X"},{"first_name":"Torsten","full_name":"Hoefler, Torsten","last_name":"Hoefler"},{"first_name":"James","full_name":"Hensman, James","last_name":"Hensman"}],"scopus_import":"1","_id":"19511"},{"acknowledgement":"Monika Henzinger: This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 101019564) and the Austrian Science Fund (FWF) grant DOI 10.55776/Z422, grant DOI 10.55776/I5982, and grant DOI 10.55776/P33775 with additional funding from the netidee SCIENCE Stiftung, 2020–2024. Joel Daniel Andersson and Rasmus Pagh are affiliated with Basic Algorithms Research Copenhagen (BARC), supported by the VILLUM Foundation grant 16582, and are also supported by Providentia, a Data Science Distinguished Investigator grant from Novo Nordisk Fonden. Teresa Anna Steiner is supported by a research grant (VIL51463) from VILLUM FONDEN. This work was done while Teresa Anna Steiner was a Postdoc at the Technical University of Denmark. Jalaj Upadhyay’s research was funded by the Rutgers Decanal Grant no. 302918 and an unrestricted gift from Google.","scopus_import":"1","_id":"19512","author":[{"last_name":"Andersson","full_name":"Andersson, Joel Daniel","first_name":"Joel Daniel"},{"first_name":"Monika H","orcid":"0000-0002-5008-6530","last_name":"Henzinger","id":"540c9bbd-f2de-11ec-812d-d04a5be85630","full_name":"Henzinger, Monika H"},{"first_name":"Rasmus","full_name":"Pagh, Rasmus","last_name":"Pagh"},{"first_name":"Teresa Anna","last_name":"Steiner","full_name":"Steiner, Teresa Anna"},{"first_name":"Jalaj","full_name":"Upadhyay, Jalaj","last_name":"Upadhyay"}],"date_created":"2025-04-06T22:01:32Z","department":[{"_id":"MoHe"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2024","corr_author":"1","OA_type":"green","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2406.03802","open_access":"1"}],"citation":{"apa":"Andersson, J. D., Henzinger, M., Pagh, R., Steiner, T. A., &#38; Upadhyay, J. (2024). Continual counting with gradual privacy expiration. In <i>38th Conference on Neural Information Processing Systems</i> (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.","ama":"Andersson JD, Henzinger M, Pagh R, Steiner TA, Upadhyay J. Continual counting with gradual privacy expiration. In: <i>38th Conference on Neural Information Processing Systems</i>. Vol 37. Neural Information Processing Systems Foundation; 2024.","mla":"Andersson, Joel Daniel, et al. “Continual Counting with Gradual Privacy Expiration.” <i>38th Conference on Neural Information Processing Systems</i>, vol. 37, Neural Information Processing Systems Foundation, 2024.","short":"J.D. Andersson, M. Henzinger, R. Pagh, T.A. Steiner, J. Upadhyay, in:, 38th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2024.","ieee":"J. D. Andersson, M. Henzinger, R. Pagh, T. A. Steiner, and J. Upadhyay, “Continual counting with gradual privacy expiration,” in <i>38th Conference on Neural Information Processing Systems</i>, Vancouver, Canada, 2024, vol. 37.","chicago":"Andersson, Joel Daniel, Monika Henzinger, Rasmus Pagh, Teresa Anna Steiner, and Jalaj Upadhyay. “Continual Counting with Gradual Privacy Expiration.” In <i>38th Conference on Neural Information Processing Systems</i>, Vol. 37. Neural Information Processing Systems Foundation, 2024.","ista":"Andersson JD, Henzinger M, Pagh R, Steiner TA, Upadhyay J. 2024. Continual counting with gradual privacy expiration. 38th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 37."},"project":[{"name":"The design and evaluation of modern fully dynamic data structures","grant_number":"101019564","call_identifier":"H2020","_id":"bd9ca328-d553-11ed-ba76-dc4f890cfe62"},{"name":"Efficient algorithms","_id":"34def286-11ca-11ed-8bc3-da5948e1613c","grant_number":"Z00422"},{"name":"Static and Dynamic Hierarchical Graph Decompositions","_id":"bda196b2-d553-11ed-ba76-8e8ee6c21103","grant_number":"I05982"},{"grant_number":"P33775","_id":"bd9e3a2e-d553-11ed-ba76-8aa684ce17fe","name":"Fast Algorithms for a Reactive Network Layer"}],"volume":37,"publisher":"Neural Information Processing Systems Foundation","oa":1,"conference":{"name":"NeurIPS: Neural Information Processing Systems","end_date":"2024-12-15","start_date":"2024-12-09","location":"Vancouver, Canada"},"OA_place":"repository","intvolume":"        37","publication_identifier":{"issn":["1049-5258"]},"quality_controlled":"1","type":"conference","month":"12","external_id":{"arxiv":["2406.03802"]},"publication":"38th Conference on Neural Information Processing Systems","status":"public","publication_status":"published","alternative_title":["Advances in Neural Information Processing Systems"],"date_updated":"2025-05-14T11:33:22Z","day":"20","oa_version":"Preprint","date_published":"2024-12-20T00:00:00Z","article_processing_charge":"No","title":"Continual counting with gradual privacy expiration","ec_funded":1,"arxiv":1,"abstract":[{"lang":"eng","text":"Differential privacy with gradual expiration models the setting where data items\r\narrive in a stream and at a given time t the privacy loss guaranteed for a data item\r\nseen at time (t − d) is εg(d), where g is a monotonically non-decreasing function.\r\nWe study the fundamental continual (binary) counting problem where each data\r\nitem consists of a bit, and the algorithm needs to output at each time step the sum of\r\nall the bits streamed so far. For a stream of length T and privacy without expiration\r\ncontinual counting is possible with maximum (over all time steps) additive error\r\nO(log2\r\n(T)/ε) and the best known lower bound is Ω(log(T)/ε); closing this gap\r\nis a challenging open problem.\r\nWe show that the situation is very different for privacy with gradual expiration by\r\ngiving upper and lower bounds for a large set of expiration functions g. Specifically,\r\nour algorithm achieves an additive error of O(log(T)/ε) for a large set of privacy\r\nexpiration functions. We also give a lower bound that shows that if C is the additive\r\nerror of any ε-DP algorithm for this problem, then the product of C and the privacy\r\nexpiration function after 2C steps must be Ω(log(T)/ε). Our algorithm matches\r\nthis lower bound as its additive error is O(log(T)/ε), even when g(2C) = O(1).\r\nOur empirical evaluation shows that we achieve a slowly growing privacy loss\r\nwith significantly smaller empirical privacy loss for large values of d than a natural\r\nbaseline algorithm."}]},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2024","OA_type":"green","corr_author":"1","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2406.14183"}],"language":[{"iso":"eng"}],"acknowledgement":"MF is supported by the MSCA IST-Bridge fellowship which has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 101034413. ER and VM are supported by the PNRR MUR project PE0000013-FAIR. MP is supported by the Sapienza grant \"Predicting and Explaining Clinical Trial Outcomes\", prot. RG12218166FA3F13.","scopus_import":"1","_id":"19515","author":[{"first_name":"Marco","id":"1c1593eb-393f-11ef-bb8e-ab4f1e979650","last_name":"Fumero","full_name":"Fumero, Marco"},{"full_name":"Pegoraro, Marco","last_name":"Pegoraro","first_name":"Marco"},{"last_name":"Maiorca","full_name":"Maiorca, Valentino","first_name":"Valentino"},{"last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","full_name":"Locatello, Francesco","first_name":"Francesco","orcid":"0000-0002-4850-0683"},{"last_name":"Rodolà","full_name":"Rodolà, Emanuele","first_name":"Emanuele"}],"date_created":"2025-04-06T22:01:32Z","department":[{"_id":"FrLo"}],"publication":"38th Conference on Neural Information Processing Systems","status":"public","publication_status":"published","oa_version":"Preprint","day":"20","alternative_title":["Advances in Neural Information Processing Systems"],"date_updated":"2025-05-14T11:36:51Z","date_published":"2024-12-20T00:00:00Z","article_processing_charge":"No","title":"Latent functional maps: A spectral framework for representation alignment","ec_funded":1,"abstract":[{"lang":"eng","text":"Neural models learn data representations that lie on low-dimensional manifolds,\r\nyet modeling the relation between these representational spaces is an ongoing challenge. By integrating spectral geometry principles into neural modeling, we show\r\nthat this problem can be better addressed in the functional domain, mitigating complexity, while enhancing interpretability and performances on downstream tasks.\r\nTo this end, we introduce a multi-purpose framework to the representation learning\r\ncommunity, which allows to: (i) compare different spaces in an interpretable way\r\nand measure their intrinsic similarity; (ii) find correspondences between them, both\r\nin unsupervised and weakly supervised settings, and (iii) to effectively transfer\r\nrepresentations between distinct spaces. We validate our framework on various\r\napplications, ranging from stitching to retrieval tasks, and on multiple modalities,\r\ndemonstrating that Latent Functional Maps can serve as a swiss-army knife for\r\nrepresentation alignment"}],"arxiv":1,"citation":{"apa":"Fumero, M., Pegoraro, M., Maiorca, V., Locatello, F., &#38; Rodolà, E. (2024). Latent functional maps: A spectral framework for representation alignment. In <i>38th Conference on Neural Information Processing Systems</i> (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.","ama":"Fumero M, Pegoraro M, Maiorca V, Locatello F, Rodolà E. Latent functional maps: A spectral framework for representation alignment. In: <i>38th Conference on Neural Information Processing Systems</i>. Vol 37. Neural Information Processing Systems Foundation; 2024.","mla":"Fumero, Marco, et al. “Latent Functional Maps: A Spectral Framework for Representation Alignment.” <i>38th Conference on Neural Information Processing Systems</i>, vol. 37, Neural Information Processing Systems Foundation, 2024.","short":"M. Fumero, M. Pegoraro, V. Maiorca, F. Locatello, E. Rodolà, in:, 38th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2024.","ieee":"M. Fumero, M. Pegoraro, V. Maiorca, F. Locatello, and E. Rodolà, “Latent functional maps: A spectral framework for representation alignment,” in <i>38th Conference on Neural Information Processing Systems</i>, Vancouver, Canada, 2024, vol. 37.","ista":"Fumero M, Pegoraro M, Maiorca V, Locatello F, Rodolà E. 2024. Latent functional maps: A spectral framework for representation alignment. 38th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 37.","chicago":"Fumero, Marco, Marco Pegoraro, Valentino Maiorca, Francesco Locatello, and Emanuele Rodolà. “Latent Functional Maps: A Spectral Framework for Representation Alignment.” In <i>38th Conference on Neural Information Processing Systems</i>, Vol. 37. Neural Information Processing Systems Foundation, 2024."},"project":[{"grant_number":"101034413","_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c","call_identifier":"H2020","name":"IST-BRIDGE: International postdoctoral program"}],"publisher":"Neural Information Processing Systems Foundation","volume":37,"oa":1,"publication_identifier":{"issn":["1049-5258"]},"intvolume":"        37","OA_place":"repository","conference":{"start_date":"2024-12-09","name":"NeurIPS: Neural Information Processing Systems","end_date":"2024-12-15","location":"Vancouver, Canada"},"quality_controlled":"1","external_id":{"arxiv":["2406.14183"]},"month":"12","type":"conference"},{"ec_funded":1,"arxiv":1,"abstract":[{"lang":"eng","text":"In this paper, we present a novel data-free method for merging neural networks in weight space. Differently from most existing works, our method optimizes for the permutations of network neurons globally across all layers. This allows us to enforce cycle consistency of the permutations when merging n ≥ 3 models, allowing circular compositions of permutations to be computed without accumulating error along the path. We qualitatively and quantitatively motivate the need for such a constraint, showing its benefits when merging sets of models in scenarios spanning varying architectures and datasets. We finally show that, when coupled\r\nwith activation renormalization, our approach yields the best results in the task."}],"title":"C2M3: Cycle-consistent multi-model merging","date_updated":"2025-05-14T11:36:59Z","day":"20","alternative_title":["Advances in Neural Information Processing Systems"],"oa_version":"Preprint","date_published":"2024-12-20T00:00:00Z","article_processing_charge":"No","publication_status":"published","publication":"38th Conference on Neural Information Processing Systems","status":"public","quality_controlled":"1","external_id":{"arxiv":["2405.17897"]},"type":"conference","month":"12","oa":1,"volume":37,"publisher":"Neural Information Processing Systems Foundation","intvolume":"        37","OA_place":"repository","conference":{"location":"Vancouver, Canada","start_date":"2024-12-09","end_date":"2024-12-15","name":"NeurIPS: Neural Information Processing Systems"},"publication_identifier":{"issn":["1049-5258"]},"project":[{"name":"IST-BRIDGE: International postdoctoral program","_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c","grant_number":"101034413","call_identifier":"H2020"}],"citation":{"apa":"Crisostomi, D., Fumero, M., Baieri, D., Bernard, F., &#38; Rodolà, E. (2024). C2M3: Cycle-consistent multi-model merging. In <i>38th Conference on Neural Information Processing Systems</i> (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.","ama":"Crisostomi D, Fumero M, Baieri D, Bernard F, Rodolà E. C2M3: Cycle-consistent multi-model merging. In: <i>38th Conference on Neural Information Processing Systems</i>. Vol 37. Neural Information Processing Systems Foundation; 2024.","mla":"Crisostomi, Donato, et al. “C2M3: Cycle-Consistent Multi-Model Merging.” <i>38th Conference on Neural Information Processing Systems</i>, vol. 37, Neural Information Processing Systems Foundation, 2024.","short":"D. Crisostomi, M. Fumero, D. Baieri, F. Bernard, E. Rodolà, in:, 38th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2024.","ieee":"D. Crisostomi, M. Fumero, D. Baieri, F. Bernard, and E. Rodolà, “C2M3: Cycle-consistent multi-model merging,” in <i>38th Conference on Neural Information Processing Systems</i>, Vancouver, Canada, 2024, vol. 37.","ista":"Crisostomi D, Fumero M, Baieri D, Bernard F, Rodolà E. 2024. C2M3: Cycle-consistent multi-model merging. 38th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 37.","chicago":"Crisostomi, Donato, Marco Fumero, Daniele Baieri, Florian Bernard, and Emanuele Rodolà. “C2M3: Cycle-Consistent Multi-Model Merging.” In <i>38th Conference on Neural Information Processing Systems</i>, Vol. 37. Neural Information Processing Systems Foundation, 2024."},"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2405.17897","open_access":"1"}],"language":[{"iso":"eng"}],"OA_type":"green","corr_author":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2024","author":[{"first_name":"Donato","full_name":"Crisostomi, Donato","last_name":"Crisostomi"},{"full_name":"Fumero, Marco","last_name":"Fumero","id":"1c1593eb-393f-11ef-bb8e-ab4f1e979650","first_name":"Marco"},{"full_name":"Baieri, Daniele","last_name":"Baieri","first_name":"Daniele"},{"full_name":"Bernard, Florian","last_name":"Bernard","first_name":"Florian"},{"full_name":"Rodolà, Emanuele","last_name":"Rodolà","first_name":"Emanuele"}],"department":[{"_id":"FrLo"}],"date_created":"2025-04-06T22:01:32Z","_id":"19517","acknowledgement":"This work is supported by the ERC grant no.802554 (SPECGEO), PRIN 2020 project\r\nno.2020TA3K9N (LEGO.AI), and PNRR MUR project PE0000013-FAIR. Marco Fumero is supported by the MSCA IST-Bridge fellowship which has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 101034413. We thank Simone Scardapane for the helpful feedback on the paper.","scopus_import":"1"},{"date_created":"2025-04-06T22:01:32Z","department":[{"_id":"DaAl"},{"_id":"MaMo"}],"author":[{"first_name":"Diyuan","full_name":"Wu, Diyuan","id":"1a5914c2-896a-11ed-bdf8-fb80621a0635","last_name":"Wu"},{"first_name":"Ionut-Vlad","full_name":"Modoranu, Ionut-Vlad","id":"449f7a18-f128-11eb-9611-9b430c0c6333","last_name":"Modoranu"},{"first_name":"Mher","full_name":"Safaryan, Mher","id":"dd546b39-0804-11ed-9c55-ef075c39778d","last_name":"Safaryan"},{"last_name":"Kuznedelev","full_name":"Kuznedelev, Denis","first_name":"Denis"},{"first_name":"Dan-Adrian","orcid":"0000-0003-3650-940X","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","last_name":"Alistarh","full_name":"Alistarh, Dan-Adrian"}],"_id":"19518","scopus_import":"1","acknowledgement":"The authors thank the anonymous NeurIPS reviewers for their useful comments and feedback, the IT department from the Institute of Science and Technology Austria for the hardware support, and Weights and Biases for the infrastructure to track all our experiments. Mher Safaryan has received funding from the European Union’s Horizon 2020 research and innovation program under the Maria Skłodowska-Curie grant agreement No 101034413.","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2408.17163","open_access":"1"}],"OA_type":"green","corr_author":"1","year":"2024","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","month":"12","external_id":{"arxiv":["2408.17163"]},"type":"conference","quality_controlled":"1","conference":{"location":"Vancouver, Canada","name":"NeurIPS: Neural Information Processing Systems","end_date":"2024-12-15","start_date":"2024-12-09"},"intvolume":"        37","OA_place":"repository","publication_identifier":{"issn":["1049-5258"]},"oa":1,"publisher":"Neural Information Processing Systems Foundation","volume":37,"project":[{"name":"IST-BRIDGE: International postdoctoral program","_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c","call_identifier":"H2020","grant_number":"101034413"}],"citation":{"ama":"Wu D, Modoranu I-V, Safaryan M, Kuznedelev D, Alistarh D-A. The iterative optimal brain surgeon: Faster sparse recovery by leveraging second-order information. In: <i>38th Conference on Neural Information Processing Systems</i>. Vol 37. Neural Information Processing Systems Foundation; 2024.","apa":"Wu, D., Modoranu, I.-V., Safaryan, M., Kuznedelev, D., &#38; Alistarh, D.-A. (2024). The iterative optimal brain surgeon: Faster sparse recovery by leveraging second-order information. In <i>38th Conference on Neural Information Processing Systems</i> (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.","ista":"Wu D, Modoranu I-V, Safaryan M, Kuznedelev D, Alistarh D-A. 2024. The iterative optimal brain surgeon: Faster sparse recovery by leveraging second-order information. 38th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 37.","chicago":"Wu, Diyuan, Ionut-Vlad Modoranu, Mher Safaryan, Denis Kuznedelev, and Dan-Adrian Alistarh. “The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information.” In <i>38th Conference on Neural Information Processing Systems</i>, Vol. 37. Neural Information Processing Systems Foundation, 2024.","ieee":"D. Wu, I.-V. Modoranu, M. Safaryan, D. Kuznedelev, and D.-A. Alistarh, “The iterative optimal brain surgeon: Faster sparse recovery by leveraging second-order information,” in <i>38th Conference on Neural Information Processing Systems</i>, Vancouver, Canada, 2024, vol. 37.","short":"D. Wu, I.-V. Modoranu, M. Safaryan, D. Kuznedelev, D.-A. Alistarh, in:, 38th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2024.","mla":"Wu, Diyuan, et al. “The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information.” <i>38th Conference on Neural Information Processing Systems</i>, vol. 37, Neural Information Processing Systems Foundation, 2024."},"arxiv":1,"abstract":[{"lang":"eng","text":"The rising footprint of machine learning has led to a focus on imposing model\r\nsparsity as a means of reducing computational and memory costs. For deep neural\r\nnetworks (DNNs), the state-of-the-art accuracy-vs-sparsity is achieved by heuristics\r\ninspired by the classical Optimal Brain Surgeon (OBS) framework [LeCun et al.,\r\n1989, Hassibi and Stork, 1992, Hassibi et al., 1993], which leverages loss curvature\r\ninformation to make better pruning decisions. Yet, these results still lack a solid\r\ntheoretical understanding, and it is unclear whether they can be improved by\r\nleveraging connections to the wealth of work on sparse recovery algorithms. In this\r\npaper, we draw new connections between these two areas and present new sparse\r\nrecovery algorithms inspired by the OBS framework that comes with theoretical\r\nguarantees under reasonable assumptions and have strong practical performance.\r\nSpecifically, our work starts from the observation that we can leverage curvature\r\ninformation in OBS-like fashion upon the projection step of classic iterative sparse\r\nrecovery algorithms such as IHT. We show for the first time that this leads both\r\nto improved convergence bounds under standard assumptions. Furthermore, we\r\npresent extensions of this approach to the practical task of obtaining accurate sparse\r\nDNNs, and validate it experimentally at scale for Transformer-based models on\r\nvision and language tasks."}],"ec_funded":1,"title":"The iterative optimal brain surgeon: Faster sparse recovery by leveraging second-order information","article_processing_charge":"No","date_published":"2024-12-20T00:00:00Z","day":"20","alternative_title":["Advances in Neural Information Processing Systems"],"date_updated":"2025-05-14T11:37:10Z","oa_version":"Preprint","acknowledged_ssus":[{"_id":"CampIT"}],"status":"public","publication_status":"published","publication":"38th Conference on Neural Information Processing Systems"},{"OA_type":"gold","file_date_updated":"2025-04-07T09:17:10Z","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2024","author":[{"last_name":"Malinovskii","full_name":"Malinovskii, Vladimir","first_name":"Vladimir"},{"full_name":"Mazur, Denis","last_name":"Mazur","first_name":"Denis"},{"first_name":"Ivan","full_name":"Ilin, Ivan","last_name":"Ilin"},{"first_name":"Denis","full_name":"Kuznedelev, Denis","last_name":"Kuznedelev"},{"first_name":"Konstantin","last_name":"Burlachenko","full_name":"Burlachenko, Konstantin"},{"first_name":"Kai","last_name":"Yi","full_name":"Yi, Kai"},{"id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","last_name":"Alistarh","full_name":"Alistarh, Dan-Adrian","first_name":"Dan-Adrian","orcid":"0000-0003-3650-940X"},{"full_name":"Richtarik, Peter","last_name":"Richtarik","first_name":"Peter"}],"date_created":"2025-04-06T22:01:32Z","department":[{"_id":"DaAl"}],"acknowledgement":"Authors would like to thank Vage Egiazarian, Andrei Panferov and Ruslan Svirschevski for their\r\nhelp and advice on AQLM codebase and running large-scale experiments. We also thank Philip\r\nZmushko and Artem Fedorov for helpful discussions during the early stages of our research. The research of Kai Yi, Konstantin Burlachenko, and Peter Richtárik reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST) – Center of Excellence for Generative AI, under award number 5940. We would also like to thank our NeurIPS reviewers for their helpful suggestions, we specifically highlight p3Lv’s suggestions to consider smaller codebook sizes and evaluate PV-Tuning with QuIP#, both of which produced interesting findings. Finally, we thank the open-source contributors from llama.cpp9 and the LocalLlama10 community for discussions and inspirations on practical use cases of quantized language models, and in particular, Yalda Shabanzadeh and Arthur Aardvark for their help with improving the codebase.","scopus_import":"1","_id":"19519","has_accepted_license":"1","ddc":["000"],"title":"PV-tuning: Beyond straight-through estimation for extreme LLM compression","arxiv":1,"abstract":[{"text":"There has been significant interest in \"extreme\" compression of large language models (LLMs), i.e. to 1-2 bits per parameter, which allows such models to be executed efficiently on resource-constrained devices. Existing work focused on improved one-shot quantization techniques and weight representations; yet, purely post-training approaches are reaching diminishing returns in terms of the accuracy-vs-bit-width trade-off. State-of-the-art quantization methods such as QuIP# and AQLM include fine-tuning (part of) the compressed parameters over a limited amount of calibration data; however, such fine-tuning techniques over compressed weights often make exclusive use of straight-through estimators (STE), whose performance is not well-understood in this setting. In this work, we question the use of STE for extreme LLM compression, showing that it can be sub-optimal, and perform a systematic study of quantization-aware fine-tuning strategies for LLMs.We propose PV-Tuning - a representation-agnostic framework that generalizes and improves upon existing fine-tuning strategies, and provides convergence guarantees in restricted cases.On the practical side, when used for 1-2 bit vector quantization, PV-Tuning outperforms prior techniques for highly-performant models such as Llama and Mistral. Using PV-Tuning, we achieve the first Pareto-optimal quantization for Llama-2 family models at 2 bits per parameter.","lang":"eng"}],"status":"public","publication":"38th Conference on Neural Information Processing Systems","publication_status":"published","day":"20","alternative_title":["Advances in Neural Information Processing Systems"],"date_updated":"2025-05-14T10:49:20Z","oa_version":"Published Version","date_published":"2024-12-20T00:00:00Z","article_processing_charge":"No","publisher":"Neural Information Processing Systems Foundation","volume":37,"oa":1,"conference":{"name":"NeurIPS: Neural Information Processing Systems","end_date":"2024-12-15","start_date":"2024-12-10","location":"Vancouver, Canada"},"intvolume":"        37","OA_place":"publisher","publication_identifier":{"isbn":["9798331314385"],"issn":["1049-5258"]},"quality_controlled":"1","type":"conference","month":"12","external_id":{"arxiv":["2405.14852"]},"file":[{"success":1,"relation":"main_file","file_size":939712,"access_level":"open_access","date_updated":"2025-04-07T09:17:10Z","file_id":"19521","file_name":"2024_NeurIPS_Malinovskii.pdf","checksum":"54d36f947887e26d0e568b512167001a","content_type":"application/pdf","date_created":"2025-04-07T09:17:10Z","creator":"dernst"}],"citation":{"chicago":"Malinovskii, Vladimir, Denis Mazur, Ivan Ilin, Denis Kuznedelev, Konstantin Burlachenko, Kai Yi, Dan-Adrian Alistarh, and Peter Richtarik. “PV-Tuning: Beyond Straight-through Estimation for Extreme LLM Compression.” In <i>38th Conference on Neural Information Processing Systems</i>, Vol. 37. Neural Information Processing Systems Foundation, 2024.","ista":"Malinovskii V, Mazur D, Ilin I, Kuznedelev D, Burlachenko K, Yi K, Alistarh D-A, Richtarik P. 2024. PV-tuning: Beyond straight-through estimation for extreme LLM compression. 38th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 37.","ieee":"V. Malinovskii <i>et al.</i>, “PV-tuning: Beyond straight-through estimation for extreme LLM compression,” in <i>38th Conference on Neural Information Processing Systems</i>, Vancouver, Canada, 2024, vol. 37.","short":"V. Malinovskii, D. Mazur, I. Ilin, D. Kuznedelev, K. Burlachenko, K. Yi, D.-A. Alistarh, P. Richtarik, in:, 38th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2024.","mla":"Malinovskii, Vladimir, et al. “PV-Tuning: Beyond Straight-through Estimation for Extreme LLM Compression.” <i>38th Conference on Neural Information Processing Systems</i>, vol. 37, Neural Information Processing Systems Foundation, 2024.","ama":"Malinovskii V, Mazur D, Ilin I, et al. PV-tuning: Beyond straight-through estimation for extreme LLM compression. In: <i>38th Conference on Neural Information Processing Systems</i>. Vol 37. Neural Information Processing Systems Foundation; 2024.","apa":"Malinovskii, V., Mazur, D., Ilin, I., Kuznedelev, D., Burlachenko, K., Yi, K., … Richtarik, P. (2024). PV-tuning: Beyond straight-through estimation for extreme LLM compression. In <i>38th Conference on Neural Information Processing Systems</i> (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation."}},{"language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.1101/2024.09.20.614050"}],"abstract":[{"text":"Vertebrates exhibit a wide range of motor behaviors, ranging from swimming to complex limb-based movements. Here we take advantage of frog metamorphosis, which captures a swim-to-limb-based movement transformation during the development of a single organism, to explore changes in the underlying spinal circuits. We find that the tadpole spinal cord contains small and largely homogeneous populations of motor neurons (MNs) and V1 interneurons (V1s) at early escape swimming stages. These neuronal populations only modestly increase in number and subtype heterogeneity with the emergence of free swimming. In contrast, during frog metamorphosis and the emergence of limb movement, there is a dramatic expansion of MN and V1 interneuron number and transcriptional heterogeneity, culminating in cohorts of neurons that exhibit striking molecular similarity to mammalian motor circuits. CRISPR/Cas9-mediated gene disruption of the limb MN and V1 determinants FoxP1 and Engrailed-1, respectively, results in severe but selective deficits in tail and limb function. Our work thus demonstrates that neural diversity scales exponentially with increasing behavioral complexity and illustrates striking evolutionary conservation in the molecular organization and function of motor circuits across species.","lang":"eng"}],"corr_author":"1","OA_type":"green","title":"Spinal neuron diversity scales exponentially with swim-to-limb transformation during frog metamorphosis","date_updated":"2025-05-14T11:40:13Z","day":"27","acknowledged_ssus":[{"_id":"Bio"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"Preprint","date_published":"2024-09-27T00:00:00Z","year":"2024","article_processing_charge":"No","status":"public","publication_status":"submitted","publication":"bioRxiv","author":[{"last_name":"Vijatovic","id":"cf391e77-ec3c-11ea-a124-d69323410b58","full_name":"Vijatovic, David","first_name":"David"},{"id":"2f73f876-f128-11eb-9611-b96b5a30cb0e","last_name":"Toma","full_name":"Toma, Florina Alexandra ","first_name":"Florina Alexandra "},{"last_name":"Harrington","id":"a8144562-32c9-11ee-b5ce-d9800628bda2","full_name":"Harrington, Zoe P","first_name":"Zoe P","orcid":"0009-0008-0158-4032"},{"last_name":"Sommer","id":"4DF26D8C-F248-11E8-B48F-1D18A9856A87","full_name":"Sommer, Christoph M","first_name":"Christoph M","orcid":"0000-0003-1216-9105"},{"orcid":"0000-0001-9843-3522","first_name":"Robert","full_name":"Hauschild, Robert","id":"4E01D6B4-F248-11E8-B48F-1D18A9856A87","last_name":"Hauschild"},{"first_name":"Alexandra J.","last_name":"Trevisan","full_name":"Trevisan, Alexandra J."},{"first_name":"Phillip","full_name":"Chapman, Phillip","last_name":"Chapman"},{"full_name":"Julseth, Mara","id":"1cf464b2-dc7d-11ea-9b2f-f9b1aa9417d1","last_name":"Julseth","first_name":"Mara"},{"first_name":"Susan","full_name":"Brenner-Morton, Susan","last_name":"Brenner-Morton"},{"last_name":"Gabitto","full_name":"Gabitto, Mariano I.","first_name":"Mariano I."},{"first_name":"Jeremy S.","last_name":"Dasen","full_name":"Dasen, Jeremy S."},{"full_name":"Bikoff, Jay B.","last_name":"Bikoff","first_name":"Jay B."},{"first_name":"Lora Beatrice Jaeger","orcid":"0000-0001-9242-5601","id":"56BE8254-C4F0-11E9-8E45-0B23E6697425","last_name":"Sweeney","full_name":"Sweeney, Lora Beatrice Jaeger"}],"month":"09","department":[{"_id":"LoSw"},{"_id":"TiVo"},{"_id":"Bio"},{"_id":"NiBa"}],"date_created":"2025-04-07T08:48:28Z","type":"preprint","oa":1,"OA_place":"repository","_id":"19520","project":[{"name":"Development of V1 interneuron diversity during swim-to-walk transition of Xenopus metamorphosis","_id":"bd73af52-d553-11ed-ba76-912049f0ac7a","grant_number":"FTI21-D-046"},{"name":"Development and Evolution of Tetrapod Motor Circuits","_id":"ebb66355-77a9-11ec-83b8-b8ac210a4dae","grant_number":"101041551"},{"grant_number":"CZI01","_id":"c08e9ad1-5a5b-11eb-8a69-9d1cf3b07473","name":"Tools for automation and feedback microscopy"}],"doi":"10.1101/2024.09.20.614050","acknowledgement":"We would like to thank the members of the Sweeney Lab (especially Stavros Papadopoulos and\r\nSophie Gobeil) for their contributions to this project and, in addition to the lab, Graziana Gatto\r\nand Mario de Bono, for discussion, and support. We are also grateful to Tom Jessell and Chris\r\nKintner for their scientific insight and mentorship during the conception of this project. This\r\nproject would also not have been possible with the technical support of the Matthias Nowak,\r\nVerena Mayer and the Aquatics as well as the Imaging and Optics Facility support teams\r\n(ISTA). In addition, we thank our funding sources for providing the resources to do these\r\nexperiments: FTI Strategy Lower Austria Dissertation Grant Number FT121-D-046 (D.V.);\r\nHorizon Europe ERC Starting Grant Number 101041551 (L.B.S., F.A.T. and D.V); Special\r\nResearch Program (SFB) of the Austrian Science Fund (FWF) Project number F7814-B (L.B.S);\r\nNINDS 5R35NS116858 (J.S.D); CZI grant DAF2020-225401 (DOI): 10.37921/120055ratwvi\r\n(R.H.); NIH grant number R01NS123116 (J.B.B); American Lebanese Syrian Associated\r\nCharities (ALSAC) (J.B.B.); German Academic Exchange Service (DAAD) IFI Grant Number\r\n57515251-91853472 (Z.H.); and Project A.L.S. (S.B-M.). ","citation":{"ieee":"D. Vijatovic <i>et al.</i>, “Spinal neuron diversity scales exponentially with swim-to-limb transformation during frog metamorphosis,” <i>bioRxiv</i>. .","chicago":"Vijatovic, David, Florina Alexandra  Toma, Zoe P Harrington, Christoph M Sommer, Robert Hauschild, Alexandra J. Trevisan, Phillip Chapman, et al. “Spinal Neuron Diversity Scales Exponentially with Swim-to-Limb Transformation during Frog Metamorphosis.” <i>BioRxiv</i>, n.d. <a href=\"https://doi.org/10.1101/2024.09.20.614050\">https://doi.org/10.1101/2024.09.20.614050</a>.","ista":"Vijatovic D, Toma FA, Harrington ZP, Sommer CM, Hauschild R, Trevisan AJ, Chapman P, Julseth M, Brenner-Morton S, Gabitto MI, Dasen JS, Bikoff JB, Sweeney LB. Spinal neuron diversity scales exponentially with swim-to-limb transformation during frog metamorphosis. bioRxiv, <a href=\"https://doi.org/10.1101/2024.09.20.614050\">10.1101/2024.09.20.614050</a>.","mla":"Vijatovic, David, et al. “Spinal Neuron Diversity Scales Exponentially with Swim-to-Limb Transformation during Frog Metamorphosis.” <i>BioRxiv</i>, doi:<a href=\"https://doi.org/10.1101/2024.09.20.614050\">10.1101/2024.09.20.614050</a>.","short":"D. Vijatovic, F.A. Toma, Z.P. Harrington, C.M. Sommer, R. Hauschild, A.J. Trevisan, P. Chapman, M. Julseth, S. Brenner-Morton, M.I. Gabitto, J.S. Dasen, J.B. Bikoff, L.B. Sweeney, BioRxiv (n.d.).","ama":"Vijatovic D, Toma FA, Harrington ZP, et al. Spinal neuron diversity scales exponentially with swim-to-limb transformation during frog metamorphosis. <i>bioRxiv</i>. doi:<a href=\"https://doi.org/10.1101/2024.09.20.614050\">10.1101/2024.09.20.614050</a>","apa":"Vijatovic, D., Toma, F. A., Harrington, Z. P., Sommer, C. M., Hauschild, R., Trevisan, A. J., … Sweeney, L. B. (n.d.). Spinal neuron diversity scales exponentially with swim-to-limb transformation during frog metamorphosis. <i>bioRxiv</i>. <a href=\"https://doi.org/10.1101/2024.09.20.614050\">https://doi.org/10.1101/2024.09.20.614050</a>"}},{"year":"2024","article_processing_charge":"No","related_material":{"record":[{"relation":"used_in_publication","id":"19796","status":"public"}]},"date_published":"2024-09-28T00:00:00Z","oa_version":"Published Version","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2025-09-30T12:46:33Z","day":"28","status":"public","abstract":[{"text":"This archive contains all the code and data necessary to reproduce the results presented in the \r\n\"Mapping the attractor landscape of Boolean networks\" paper.","lang":"eng"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.5281/zenodo.13854760"}],"title":"Mapping the attractor landscape of Boolean networks","OA_type":"green","ddc":["000"],"doi":"10.5281/ZENODO.13854759","has_accepted_license":"1","_id":"19800","citation":{"ama":"trinh VG, Park KH, Pastva S, Rozum J. Mapping the attractor landscape of Boolean networks. 2024. doi:<a href=\"https://doi.org/10.5281/ZENODO.13854759\">10.5281/ZENODO.13854759</a>","apa":"trinh, V. G., Park, K. H., Pastva, S., &#38; Rozum, J. (2024). Mapping the attractor landscape of Boolean networks. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.13854759\">https://doi.org/10.5281/ZENODO.13854759</a>","ieee":"V. G. trinh, K. H. Park, S. Pastva, and J. Rozum, “Mapping the attractor landscape of Boolean networks.” Zenodo, 2024.","ista":"trinh VG, Park KH, Pastva S, Rozum J. 2024. Mapping the attractor landscape of Boolean networks, Zenodo, <a href=\"https://doi.org/10.5281/ZENODO.13854759\">10.5281/ZENODO.13854759</a>.","chicago":"trinh, Van Giang, Kyu Hyong Park, Samuel Pastva, and Jordan Rozum. “Mapping the Attractor Landscape of Boolean Networks.” Zenodo, 2024. <a href=\"https://doi.org/10.5281/ZENODO.13854759\">https://doi.org/10.5281/ZENODO.13854759</a>.","mla":"trinh, Van Giang, et al. <i>Mapping the Attractor Landscape of Boolean Networks</i>. Zenodo, 2024, doi:<a href=\"https://doi.org/10.5281/ZENODO.13854759\">10.5281/ZENODO.13854759</a>.","short":"V.G. trinh, K.H. Park, S. Pastva, J. Rozum, (2024)."},"type":"research_data_reference","date_created":"2025-06-10T07:10:01Z","month":"09","department":[{"_id":"ToHe"}],"author":[{"first_name":"Van Giang","last_name":"trinh","full_name":"trinh, Van Giang"},{"last_name":"Park","full_name":"Park, Kyu Hyong","first_name":"Kyu Hyong"},{"last_name":"Pastva","id":"07c5ea74-f61c-11ec-a664-aa7c5d957b2b","full_name":"Pastva, Samuel","first_name":"Samuel","orcid":"0000-0003-1993-0331"},{"full_name":"Rozum, Jordan","last_name":"Rozum","first_name":"Jordan"}],"OA_place":"repository","publisher":"Zenodo","tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"oa":1},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2024","main_file_link":[{"url":"https://doi.org/10.1073/pnas.2318159121","open_access":"1"}],"language":[{"iso":"eng"}],"OA_type":"hybrid","_id":"19809","doi":"10.1073/pnas.2318159121","has_accepted_license":"1","issue":"35","scopus_import":"1","author":[{"first_name":"Fei","full_name":"Sun, Fei","last_name":"Sun"},{"full_name":"Mishra, Simli","last_name":"Mishra","first_name":"Simli"},{"full_name":"Stockert, Ulrike","last_name":"Stockert","first_name":"Ulrike"},{"last_name":"Daou","full_name":"Daou, Ramzy","first_name":"Ramzy"},{"first_name":"Naoki","last_name":"Kikugawa","full_name":"Kikugawa, Naoki"},{"full_name":"Perry, Robin S.","last_name":"Perry","first_name":"Robin S."},{"full_name":"Hassinger, Elena","last_name":"Hassinger","first_name":"Elena"},{"first_name":"Sean A.","full_name":"Hartnoll, Sean A.","last_name":"Hartnoll"},{"first_name":"Andrew P.","full_name":"Mackenzie, Andrew P.","last_name":"Mackenzie"},{"full_name":"Sunko, Veronika","last_name":"Sunko","id":"23cb1cf6-2c7a-11ef-91a4-f72fc19f20b3","orcid":"0000-0003-2724-3523","first_name":"Veronika"}],"date_created":"2025-06-10T09:12:41Z","date_updated":"2025-06-10T11:50:48Z","day":"27","oa_version":"Published Version","date_published":"2024-08-27T00:00:00Z","article_processing_charge":"No","publication_status":"published","publication":"Proceedings of the National Academy of Sciences","status":"public","abstract":[{"text":"In many physical situations in which many-body assemblies exist at temperature T, a characteristic quantum-mechanical time scale of approximately h/kbT can be identified in both theory and experiment, leading to speculation that it may be the shortest meaningful time in such circumstances. This behavior can be investigated by probing the scattering rate of electrons in a broad class of materials often referred to as “strongly correlated metals”. It is clear that in some cases only electron–electron scattering can be its cause, while in others it arises from high-temperature scattering of electrons from quantized lattice vibrations, i.e., phonons. In metallic oxides, which are among the most studied materials, analysis of electrical transport does not satisfactorily identify the relevant scattering mechanism at “high” temperatures near room temperature. We therefore employ a contactless optical method to measure thermal diffusivity in two Ru-based layered perovskites, Sr3Ru2O7 and Sr2RuO4, and use the measurements to extract the dimensionless Lorenz ratio. By comparing our results to the literature data on both conventional and unconventional metals, we show how the analysis of high-temperature thermal transport can both give important insight into dominant scattering mechanisms and be offered as a stringent test of theories attempting to explain anomalous scattering.","lang":"eng"}],"title":"The Lorenz ratio as a guide to scattering contributions to transport in strongly correlated metals","article_type":"original","citation":{"apa":"Sun, F., Mishra, S., Stockert, U., Daou, R., Kikugawa, N., Perry, R. S., … Sunko, V. (2024). The Lorenz ratio as a guide to scattering contributions to transport in strongly correlated metals. <i>Proceedings of the National Academy of Sciences</i>. National Academy of Sciences. <a href=\"https://doi.org/10.1073/pnas.2318159121\">https://doi.org/10.1073/pnas.2318159121</a>","ama":"Sun F, Mishra S, Stockert U, et al. The Lorenz ratio as a guide to scattering contributions to transport in strongly correlated metals. <i>Proceedings of the National Academy of Sciences</i>. 2024;121(35). doi:<a href=\"https://doi.org/10.1073/pnas.2318159121\">10.1073/pnas.2318159121</a>","mla":"Sun, Fei, et al. “The Lorenz Ratio as a Guide to Scattering Contributions to Transport in Strongly Correlated Metals.” <i>Proceedings of the National Academy of Sciences</i>, vol. 121, no. 35, National Academy of Sciences, 2024, doi:<a href=\"https://doi.org/10.1073/pnas.2318159121\">10.1073/pnas.2318159121</a>.","short":"F. Sun, S. Mishra, U. Stockert, R. Daou, N. Kikugawa, R.S. Perry, E. Hassinger, S.A. Hartnoll, A.P. Mackenzie, V. Sunko, Proceedings of the National Academy of Sciences 121 (2024).","ieee":"F. Sun <i>et al.</i>, “The Lorenz ratio as a guide to scattering contributions to transport in strongly correlated metals,” <i>Proceedings of the National Academy of Sciences</i>, vol. 121, no. 35. National Academy of Sciences, 2024.","chicago":"Sun, Fei, Simli Mishra, Ulrike Stockert, Ramzy Daou, Naoki Kikugawa, Robin S. Perry, Elena Hassinger, Sean A. Hartnoll, Andrew P. Mackenzie, and Veronika Sunko. “The Lorenz Ratio as a Guide to Scattering Contributions to Transport in Strongly Correlated Metals.” <i>Proceedings of the National Academy of Sciences</i>. National Academy of Sciences, 2024. <a href=\"https://doi.org/10.1073/pnas.2318159121\">https://doi.org/10.1073/pnas.2318159121</a>.","ista":"Sun F, Mishra S, Stockert U, Daou R, Kikugawa N, Perry RS, Hassinger E, Hartnoll SA, Mackenzie AP, Sunko V. 2024. The Lorenz ratio as a guide to scattering contributions to transport in strongly correlated metals. Proceedings of the National Academy of Sciences. 121(35)."},"pmid":1,"extern":"1","quality_controlled":"1","month":"08","type":"journal_article","external_id":{"pmid":["39172781"]},"oa":1,"tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"volume":121,"publisher":"National Academy of Sciences","intvolume":"       121","OA_place":"publisher","publication_identifier":{"issn":["0027-8424"],"eissn":["1091-6490"]}},{"type":"journal_article","month":"07","quality_controlled":"1","extern":"1","publication_identifier":{"eissn":["2160-3308"]},"intvolume":"        14","OA_place":"publisher","publisher":"American Physical Society","oa":1,"volume":14,"article_type":"original","citation":{"ieee":"E. Donoway <i>et al.</i>, “Multimodal approach reveals the symmetry-breaking pathway to the broken helix in EuIn2As2,” <i>Physical Review X</i>, vol. 14, no. 3. American Physical Society, 2024.","chicago":"Donoway, E., T. V. Trevisan, A. Liebman-Peláez, R. P. Day, K. Yamakawa, Y. Sun, J. R. Soh, et al. “Multimodal Approach Reveals the Symmetry-Breaking Pathway to the Broken Helix in EuIn2As2.” <i>Physical Review X</i>. American Physical Society, 2024. <a href=\"https://doi.org/10.1103/physrevx.14.031013\">https://doi.org/10.1103/physrevx.14.031013</a>.","ista":"Donoway E, Trevisan TV, Liebman-Peláez A, Day RP, Yamakawa K, Sun Y, Soh JR, Prabhakaran D, Boothroyd AT, Fernandes RM, Analytis JG, Moore JE, Orenstein J, Sunko V. 2024. Multimodal approach reveals the symmetry-breaking pathway to the broken helix in EuIn2As2. Physical Review X. 14(3), 031013.","mla":"Donoway, E., et al. “Multimodal Approach Reveals the Symmetry-Breaking Pathway to the Broken Helix in EuIn2As2.” <i>Physical Review X</i>, vol. 14, no. 3, 031013, American Physical Society, 2024, doi:<a href=\"https://doi.org/10.1103/physrevx.14.031013\">10.1103/physrevx.14.031013</a>.","short":"E. Donoway, T.V. Trevisan, A. Liebman-Peláez, R.P. Day, K. Yamakawa, Y. Sun, J.R. Soh, D. Prabhakaran, A.T. Boothroyd, R.M. Fernandes, J.G. Analytis, J.E. Moore, J. Orenstein, V. Sunko, Physical Review X 14 (2024).","ama":"Donoway E, Trevisan TV, Liebman-Peláez A, et al. Multimodal approach reveals the symmetry-breaking pathway to the broken helix in EuIn2As2. <i>Physical Review X</i>. 2024;14(3). doi:<a href=\"https://doi.org/10.1103/physrevx.14.031013\">10.1103/physrevx.14.031013</a>","apa":"Donoway, E., Trevisan, T. V., Liebman-Peláez, A., Day, R. P., Yamakawa, K., Sun, Y., … Sunko, V. (2024). Multimodal approach reveals the symmetry-breaking pathway to the broken helix in EuIn2As2. <i>Physical Review X</i>. American Physical Society. <a href=\"https://doi.org/10.1103/physrevx.14.031013\">https://doi.org/10.1103/physrevx.14.031013</a>"},"abstract":[{"lang":"eng","text":"Understanding and manipulating emergent phases, which are themes at the forefront of quantum-materials research, rely on identifying their underlying symmetries. This general principle has been particularly prominent in materials with coupled electronic and magnetic degrees of freedom, in which magnetic order influences the electronic band structure and can lead to exotic topological effects. However, identifying symmetry of a magnetically ordered phase can pose a challenge, particularly in the presence of small domains. Here we introduce a multimodal approach for determining magnetic structures, which combines symmetry-sensitive optical probes, scattering, and group-theoretical analysis. We apply it to EuIn2⁢As2, a material that has received attention as a candidate axion insulator. While first-principles calculations predict this state on the assumption of a simple collinear antiferromagnetic structure, subsequent neutron-scattering measurements reveal a much more intricate magnetic ground state characterized by two coexisting magnetic wave vectors reached by successive thermal phase transitions. The proposed high- and low-temperature phases are a spin helix and a state with interpenetrating helical and Néel antiferromagnetic order termed a “broken helix,” respectively. Employing a multimodal approach, we identify the magnetic structure associated with these two phases of EuIn2⁢As2. We find that the higher-temperature phase is characterized by a variation of the magnetic moment amplitude from layer to layer, with the moment vanishing entirely in every third Eu layer. The lower-temperature structure is similar to the broken helix, with one important difference: Because of local strain, the relative orientation of the magnetic structure and the lattice is not fixed. Consequently, the symmetry required to protect the axion phase is not generically protected in EuIn2⁢As2, but we show that it can be restored if the magnetic structure is tuned with uniaxial strain. Finally, we present a spin Hamiltonian that identifies the spin interactions that account for the complex magnetic order in EuIn2⁢As2. Our work highlights the importance of a multimodal approach in determining the symmetry of complex order parameters."}],"title":"Multimodal approach reveals the symmetry-breaking pathway to the broken helix in EuIn2As2","article_processing_charge":"No","date_published":"2024-07-22T00:00:00Z","oa_version":"Published Version","day":"22","date_updated":"2025-06-10T13:14:20Z","publication_status":"published","status":"public","publication":"Physical Review X","date_created":"2025-06-10T09:17:30Z","author":[{"first_name":"E.","last_name":"Donoway","full_name":"Donoway, E."},{"first_name":"T. V.","last_name":"Trevisan","full_name":"Trevisan, T. V."},{"last_name":"Liebman-Peláez","full_name":"Liebman-Peláez, A.","first_name":"A."},{"first_name":"R. P.","last_name":"Day","full_name":"Day, R. P."},{"first_name":"K.","last_name":"Yamakawa","full_name":"Yamakawa, K."},{"full_name":"Sun, Y.","last_name":"Sun","first_name":"Y."},{"full_name":"Soh, J. R.","last_name":"Soh","first_name":"J. R."},{"first_name":"D.","full_name":"Prabhakaran, D.","last_name":"Prabhakaran"},{"first_name":"A. T.","full_name":"Boothroyd, A. T.","last_name":"Boothroyd"},{"first_name":"R. M.","full_name":"Fernandes, R. M.","last_name":"Fernandes"},{"last_name":"Analytis","full_name":"Analytis, J. G.","first_name":"J. G."},{"last_name":"Moore","full_name":"Moore, J. E.","first_name":"J. E."},{"first_name":"J.","full_name":"Orenstein, J.","last_name":"Orenstein"},{"orcid":"0000-0003-2724-3523","first_name":"Veronika","full_name":"Sunko, Veronika","last_name":"Sunko","id":"23cb1cf6-2c7a-11ef-91a4-f72fc19f20b3"}],"doi":"10.1103/physrevx.14.031013","_id":"19816","DOAJ_listed":"1","scopus_import":"1","issue":"3","main_file_link":[{"url":"https://doi.org/10.1103/physrevx.14.031013","open_access":"1"}],"language":[{"iso":"eng"}],"OA_type":"gold","year":"2024","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_number":"031013"},{"date_updated":"2025-09-30T13:41:56Z","day":"24","oa_version":"Published Version","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","related_material":{"record":[{"id":"19877","relation":"used_for_analysis_in","status":"public"}]},"date_published":"2024-11-24T00:00:00Z","year":"2024","article_processing_charge":"No","status":"public","main_file_link":[{"url":"https://doi.org/10.5281/ZENODO.14213091","open_access":"1"}],"abstract":[{"lang":"eng","text":"This is Marlin, a Mixed Auto-Regressive Linear kernel (and the name of one of the planet's fastest fish), an extremely optimized FP16xINT4 matmul kernel aimed at LLM inference that can deliver close to ideal (4x) speedups up to batchsizes of 16-32 tokens (in contrast to the 1-2 tokens of prior work with comparable speedup).\r\n\r\nAdditionally, it includes Sparse-Marlin, an extension of the MARLIN kernels adding support to 2:4 weight sparsity, achieving 5.3x speedups on NVIDIA GPUs (Ampere/Ada)."}],"ddc":["000"],"title":"MARLIN: Mixed-precision auto-regressive parallel inference on Large Language Models","corr_author":"1","_id":"19884","has_accepted_license":"1","doi":"10.5281/ZENODO.14213091","citation":{"short":"E. Frantar, R. Castro, J. Chen, T. Hoefler, D.-A. Alistarh, (2024).","mla":"Frantar, Elias, et al. <i>MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models</i>. Zenodo, 2024, doi:<a href=\"https://doi.org/10.5281/ZENODO.14213091\">10.5281/ZENODO.14213091</a>.","ista":"Frantar E, Castro R, Chen J, Hoefler T, Alistarh D-A. 2024. MARLIN: Mixed-precision auto-regressive parallel inference on Large Language Models, Zenodo, <a href=\"https://doi.org/10.5281/ZENODO.14213091\">10.5281/ZENODO.14213091</a>.","chicago":"Frantar, Elias, Roberto Castro, Jiale Chen, Torsten Hoefler, and Dan-Adrian Alistarh. “MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models.” Zenodo, 2024. <a href=\"https://doi.org/10.5281/ZENODO.14213091\">https://doi.org/10.5281/ZENODO.14213091</a>.","ieee":"E. Frantar, R. Castro, J. Chen, T. Hoefler, and D.-A. Alistarh, “MARLIN: Mixed-precision auto-regressive parallel inference on Large Language Models.” Zenodo, 2024.","apa":"Frantar, E., Castro, R., Chen, J., Hoefler, T., &#38; Alistarh, D.-A. (2024). MARLIN: Mixed-precision auto-regressive parallel inference on Large Language Models. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.14213091\">https://doi.org/10.5281/ZENODO.14213091</a>","ama":"Frantar E, Castro R, Chen J, Hoefler T, Alistarh D-A. MARLIN: Mixed-precision auto-regressive parallel inference on Large Language Models. 2024. doi:<a href=\"https://doi.org/10.5281/ZENODO.14213091\">10.5281/ZENODO.14213091</a>"},"author":[{"first_name":"Elias","full_name":"Frantar, Elias","id":"09a8f98d-ec99-11ea-ae11-c063a7b7fe5f","last_name":"Frantar"},{"first_name":"Roberto","full_name":"Castro, Roberto","last_name":"Castro"},{"last_name":"Chen","id":"4d0a9064-1ff6-11ee-9fa6-ec046c604785","full_name":"Chen, Jiale","first_name":"Jiale","orcid":"0000-0001-5337-5875"},{"first_name":"Torsten","last_name":"Hoefler","full_name":"Hoefler, Torsten"},{"first_name":"Dan-Adrian","orcid":"0000-0003-3650-940X","last_name":"Alistarh","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","full_name":"Alistarh, Dan-Adrian"}],"date_created":"2025-06-24T06:09:18Z","department":[{"_id":"DaAl"}],"type":"research_data_reference","month":"11","publisher":"Zenodo","tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"oa":1,"OA_place":"repository"},{"status":"public","publication":"Nature Mental Health","publication_status":"published","article_processing_charge":"No","date_published":"2024-10-01T00:00:00Z","day":"01","date_updated":"2025-07-22T08:59:10Z","oa_version":"None","title":"A protocol for data harmonization in large cohorts","abstract":[{"lang":"eng","text":"This Comment presents a high-level protocol for data harmonization within large cohorts, in which it postulates four main steps including (1) expert review, (2) pre-statistical harmonization, (3) statistical harmonization, and (4) validation."}],"citation":{"apa":"Neidhart, M., Kjelkenes, R., Jansone, K., Rehák Bučková, B., Holz, N., Nees, F., … Heinz, A. (2024). A protocol for data harmonization in large cohorts. <i>Nature Mental Health</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s44220-024-00315-0\">https://doi.org/10.1038/s44220-024-00315-0</a>","ama":"Neidhart M, Kjelkenes R, Jansone K, et al. A protocol for data harmonization in large cohorts. <i>Nature Mental Health</i>. 2024;2(10):1134-1137. doi:<a href=\"https://doi.org/10.1038/s44220-024-00315-0\">10.1038/s44220-024-00315-0</a>","short":"M. Neidhart, R. Kjelkenes, K. Jansone, B. Rehák Bučková, N. Holz, F. Nees, H. Walter, G. Schumann, M.A. Rapp, T. Banaschewski, E. Schwarz, A. Marquand, G. Ogoh, B. Stahl, A.H. Young, S. Desrivières, N. Clinton, P. Thompson, A. Schwalber, J. Liu, V. Calhoun, X. Chang, Y. Xia, Y. Gong, T. Jia, P. Renner, S. Hese, A. Giner, M. Sanchez, E. Alvarez, B. Spanlang, C. Pearmund, A.P. Athanasiadis, L. Otten, S. Pitel, S. Petkoski, V. Jirsa, K. Schmitt, J. Wilbertz, M. Patraskaki, P. Sommer, S. Heilmann-Heimbach, C.M. Mathey, A. Miller, I. Claus, M.M. Nöthen, P. Hoffmann, A.J. Forstner, A. Pastor, J. Gallego, F.E. Orosa, G.F. Viapiana, M. Slater, L. Marr, G. Novarino, S.J. Böttger, M. Tschorn, M. Rapp, H. Ask, S. Fernandez, D. Van Der Meer, L.T. Westlye, O.A. Andreassen, R. Aden, B. Seefried, S. Siehl, F. Nees, A. Stringaris, H. Tost, A. Meyer-Lindenberg, N. Christmann, J. Banks, K. Schepanski, T. Schütz, U.H. Taron, R. Eils, J.C. Roy, T.A. Lett, H. Kebir, E. Polemiti, E. Hitchen, M. Jentsch, E. Serin, A. Bernas, N. Vaidya, S. Twardziok, M. Ralser, A. Heinz, Nature Mental Health 2 (2024) 1134–1137.","mla":"Neidhart, Maja, et al. “A Protocol for Data Harmonization in Large Cohorts.” <i>Nature Mental Health</i>, vol. 2, no. 10, Springer Nature, 2024, pp. 1134–37, doi:<a href=\"https://doi.org/10.1038/s44220-024-00315-0\">10.1038/s44220-024-00315-0</a>.","ista":"Neidhart M, Kjelkenes R, Jansone K, Rehák Bučková B, Holz N, Nees F, Walter H, Schumann G, Rapp MA, Banaschewski T, Schwarz E, Marquand A, Ogoh G, Stahl B, Young AH, Desrivières S, Clinton N, Thompson P, Schwalber A, Liu J, Calhoun V, Chang X, Xia Y, Gong Y, Jia T, Renner P, Hese S, Giner A, Sanchez M, Alvarez E, Spanlang B, Pearmund C, Athanasiadis AP, Otten L, Pitel S, Petkoski S, Jirsa V, Schmitt K, Wilbertz J, Patraskaki M, Sommer P, Heilmann-Heimbach S, Mathey CM, Miller A, Claus I, Nöthen MM, Hoffmann P, Forstner AJ, Pastor A, Gallego J, Orosa FE, Viapiana GF, Slater M, Marr L, Novarino G, Böttger SJ, Tschorn M, Rapp M, Ask H, Fernandez S, Van Der Meer D, Westlye LT, Andreassen OA, Aden R, Seefried B, Siehl S, Nees F, Stringaris A, Tost H, Meyer-Lindenberg A, Christmann N, Banks J, Schepanski K, Schütz T, Taron UH, Eils R, Roy JC, Lett TA, Kebir H, Polemiti E, Hitchen E, Jentsch M, Serin E, Bernas A, Vaidya N, Twardziok S, Ralser M, Heinz A. 2024. A protocol for data harmonization in large cohorts. Nature Mental Health. 2(10), 1134–1137.","chicago":"Neidhart, Maja, Rikka Kjelkenes, Karina Jansone, Barbora Rehák Bučková, Nathalie Holz, Frauke Nees, Henrik Walter, et al. “A Protocol for Data Harmonization in Large Cohorts.” <i>Nature Mental Health</i>. Springer Nature, 2024. <a href=\"https://doi.org/10.1038/s44220-024-00315-0\">https://doi.org/10.1038/s44220-024-00315-0</a>.","ieee":"M. Neidhart <i>et al.</i>, “A protocol for data harmonization in large cohorts,” <i>Nature Mental Health</i>, vol. 2, no. 10. Springer Nature, pp. 1134–1137, 2024."},"article_type":"comment","intvolume":"         2","publication_identifier":{"eissn":["2731-6076"]},"publisher":"Springer Nature","volume":2,"month":"10","type":"journal_article","page":"1134-1137","quality_controlled":"1","year":"2024","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","OA_type":"closed access","language":[{"iso":"eng"}],"scopus_import":"1","acknowledgement":"Funded by the European Union. Complementary funding was received by UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee (10041392 and 10038599). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union, the European Health and Digital Executive Agency (HADEA) or UKRI. The European Union, HADEA or UKRI cannot be held responsible for them. This work received support from the Chinese Ministry for Science and Technology (MOST), the Horizon 2020-funded European Research Council advanced grant ‘STRATIFY’ (695313); the German Research Foundation (COPE; 675346; NE 1383/15-1 and BA 2088/7-1 (CoviDrug)), the National Natural Science Foundation of China grant 82150710554, the Hector II foundation and the German Center for Mental Health (DZPG) (01EE2301A, 01EE2304A, 01EE2301D).","issue":"10","doi":"10.1038/s44220-024-00315-0","_id":"20039","date_created":"2025-07-20T22:02:04Z","department":[{"_id":"GaNo"}],"author":[{"first_name":"Maja","last_name":"Neidhart","full_name":"Neidhart, Maja"},{"first_name":"Rikka","last_name":"Kjelkenes","full_name":"Kjelkenes, Rikka"},{"first_name":"Karina","full_name":"Jansone, Karina","last_name":"Jansone"},{"last_name":"Rehák Bučková","full_name":"Rehák Bučková, Barbora","first_name":"Barbora"},{"first_name":"Nathalie","full_name":"Holz, Nathalie","last_name":"Holz"},{"full_name":"Nees, Frauke","last_name":"Nees","first_name":"Frauke"},{"full_name":"Walter, Henrik","last_name":"Walter","first_name":"Henrik"},{"first_name":"Gunter","last_name":"Schumann","full_name":"Schumann, Gunter"},{"first_name":"Michael A.","full_name":"Rapp, Michael A.","last_name":"Rapp"},{"first_name":"Tobias","last_name":"Banaschewski","full_name":"Banaschewski, Tobias"},{"full_name":"Schwarz, Emanuel","last_name":"Schwarz","first_name":"Emanuel"},{"first_name":"Andre","last_name":"Marquand","full_name":"Marquand, Andre"},{"first_name":"George","last_name":"Ogoh","full_name":"Ogoh, George"},{"first_name":"Bernd","last_name":"Stahl","full_name":"Stahl, Bernd"},{"full_name":"Young, Allan H.","last_name":"Young","first_name":"Allan H."},{"first_name":"Sylvane","last_name":"Desrivières","full_name":"Desrivières, Sylvane"},{"first_name":"Nicholas","full_name":"Clinton, Nicholas","last_name":"Clinton"},{"first_name":"Paul","full_name":"Thompson, Paul","last_name":"Thompson"},{"full_name":"Schwalber, Ameli","last_name":"Schwalber","first_name":"Ameli"},{"first_name":"Jingyu","full_name":"Liu, Jingyu","last_name":"Liu"},{"first_name":"Vince","last_name":"Calhoun","full_name":"Calhoun, Vince"},{"full_name":"Chang, Xiao","last_name":"Chang","first_name":"Xiao"},{"last_name":"Xia","full_name":"Xia, Yunman","first_name":"Yunman"},{"first_name":"Yanting","last_name":"Gong","full_name":"Gong, Yanting"},{"first_name":"Tianye","last_name":"Jia","full_name":"Jia, Tianye"},{"last_name":"Renner","full_name":"Renner, Paul","first_name":"Paul"},{"first_name":"Sören","last_name":"Hese","full_name":"Hese, Sören"},{"full_name":"Giner, Arantxa","last_name":"Giner","first_name":"Arantxa"},{"first_name":"Mavi","last_name":"Sanchez","full_name":"Sanchez, Mavi"},{"first_name":"Elena","last_name":"Alvarez","full_name":"Alvarez, Elena"},{"last_name":"Spanlang","full_name":"Spanlang, Bernhard","first_name":"Bernhard"},{"full_name":"Pearmund, Charlie","last_name":"Pearmund","first_name":"Charlie"},{"full_name":"Athanasiadis, Anastasios Polykarpos","last_name":"Athanasiadis","first_name":"Anastasios Polykarpos"},{"full_name":"Otten, Lisa","last_name":"Otten","first_name":"Lisa"},{"full_name":"Pitel, Séverine","last_name":"Pitel","first_name":"Séverine"},{"first_name":"Spase","last_name":"Petkoski","full_name":"Petkoski, Spase"},{"first_name":"Viktor","last_name":"Jirsa","full_name":"Jirsa, Viktor"},{"first_name":"Karen","full_name":"Schmitt, Karen","last_name":"Schmitt"},{"full_name":"Wilbertz, Johannes","last_name":"Wilbertz","first_name":"Johannes"},{"full_name":"Patraskaki, Myrto","last_name":"Patraskaki","first_name":"Myrto"},{"first_name":"Peter","last_name":"Sommer","full_name":"Sommer, Peter"},{"last_name":"Heilmann-Heimbach","full_name":"Heilmann-Heimbach, Stefanie","first_name":"Stefanie"},{"first_name":"Carina M.","full_name":"Mathey, Carina M.","last_name":"Mathey"},{"first_name":"Abigail","full_name":"Miller, Abigail","last_name":"Miller"},{"first_name":"Isabelle","full_name":"Claus, Isabelle","last_name":"Claus"},{"first_name":"Markus M.","last_name":"Nöthen","full_name":"Nöthen, Markus M."},{"first_name":"Per","full_name":"Hoffmann, Per","last_name":"Hoffmann"},{"first_name":"Andreas J.","last_name":"Forstner","full_name":"Forstner, Andreas J."},{"last_name":"Pastor","full_name":"Pastor, Alvaro","first_name":"Alvaro"},{"first_name":"Jaime","last_name":"Gallego","full_name":"Gallego, Jaime"},{"first_name":"Francisco Eiroa","last_name":"Orosa","full_name":"Orosa, Francisco Eiroa"},{"full_name":"Viapiana, Guillem Feixas","last_name":"Viapiana","first_name":"Guillem Feixas"},{"full_name":"Slater, Mel","last_name":"Slater","first_name":"Mel"},{"last_name":"Marr","id":"4406F586-F248-11E8-B48F-1D18A9856A87","full_name":"Marr, Lena","first_name":"Lena"},{"first_name":"Gaia","orcid":"0000-0002-7673-7178","id":"3E57A680-F248-11E8-B48F-1D18A9856A87","last_name":"Novarino","full_name":"Novarino, Gaia"},{"last_name":"Böttger","full_name":"Böttger, Sarah Jane","first_name":"Sarah Jane"},{"full_name":"Tschorn, Mira","last_name":"Tschorn","first_name":"Mira"},{"first_name":"Michael","last_name":"Rapp","full_name":"Rapp, Michael"},{"first_name":"Helga","full_name":"Ask, Helga","last_name":"Ask"},{"full_name":"Fernandez, Sara","last_name":"Fernandez","first_name":"Sara"},{"full_name":"Van Der Meer, Dennis","last_name":"Van Der Meer","first_name":"Dennis"},{"full_name":"Westlye, Lars T.","last_name":"Westlye","first_name":"Lars T."},{"first_name":"Ole A.","last_name":"Andreassen","full_name":"Andreassen, Ole A."},{"last_name":"Aden","full_name":"Aden, Rieke","first_name":"Rieke"},{"full_name":"Seefried, Beke","last_name":"Seefried","first_name":"Beke"},{"first_name":"Sebastian","full_name":"Siehl, Sebastian","last_name":"Siehl"},{"first_name":"Frauke","last_name":"Nees","full_name":"Nees, Frauke"},{"first_name":"Argyris","last_name":"Stringaris","full_name":"Stringaris, Argyris"},{"first_name":"Heike","last_name":"Tost","full_name":"Tost, Heike"},{"last_name":"Meyer-Lindenberg","full_name":"Meyer-Lindenberg, Andreas","first_name":"Andreas"},{"full_name":"Christmann, Nina","last_name":"Christmann","first_name":"Nina"},{"full_name":"Banks, Jamie","last_name":"Banks","first_name":"Jamie"},{"first_name":"Kerstin","last_name":"Schepanski","full_name":"Schepanski, Kerstin"},{"last_name":"Schütz","full_name":"Schütz, Tatjana","first_name":"Tatjana"},{"first_name":"Ulrike Helene","full_name":"Taron, Ulrike Helene","last_name":"Taron"},{"last_name":"Eils","full_name":"Eils, Roland","first_name":"Roland"},{"last_name":"Roy","full_name":"Roy, Jean Charles","first_name":"Jean Charles"},{"last_name":"Lett","full_name":"Lett, Tristram A.","first_name":"Tristram A."},{"first_name":"Hedi","full_name":"Kebir, Hedi","last_name":"Kebir"},{"last_name":"Polemiti","full_name":"Polemiti, Elli","first_name":"Elli"},{"full_name":"Hitchen, Esther","last_name":"Hitchen","first_name":"Esther"},{"first_name":"Marcel","last_name":"Jentsch","full_name":"Jentsch, Marcel"},{"first_name":"Emin","full_name":"Serin, Emin","last_name":"Serin"},{"first_name":"Antoine","last_name":"Bernas","full_name":"Bernas, Antoine"},{"last_name":"Vaidya","full_name":"Vaidya, Nilakshi","first_name":"Nilakshi"},{"last_name":"Twardziok","full_name":"Twardziok, Sven","first_name":"Sven"},{"last_name":"Ralser","full_name":"Ralser, Markus","first_name":"Markus"},{"first_name":"Andreas","last_name":"Heinz","full_name":"Heinz, Andreas"}]},{"oa_version":"Published Version","day":"04","date_updated":"2026-06-18T18:19:28Z","article_processing_charge":"No","date_published":"2024-01-04T00:00:00Z","publication":"Advanced Materials","status":"public","publication_status":"published","abstract":[{"text":"In article number 2305128, Qing Sun, Shang Wang, Yanhong Tian, Andreu Cabot, and co-workers report an investigation of the energy-storage mechanism of a layered Bi2Te3-based cathode for aqueous zinc-ion batteries (ZIBs). They demonstrate that the zinc ion is not inserted into the cathode as previously assumed; in contrast, proton charge-storage dominates the process. They also demonstrate the great application prospects of aqueous ZIBs in flexible electronics via jet printing technology.","lang":"eng"}],"title":"A layered Bi2Te3@PPy cathode for aqueous Zinc‐Ion batteries: Mechanism and application in printed flexible batteries","ddc":["530"],"citation":{"chicago":"Zeng, Guifang, Qing Sun, Sharona Horta, Shang Wang, Xuan Lu, Chao Yue Zhang, Jing Li, et al. <i>A Layered Bi2Te3@PPy Cathode for Aqueous Zinc‐Ion Batteries: Mechanism and Application in Printed Flexible Batteries</i>. <i>Advanced Materials</i>. Vol. 36. Wiley, 2024. <a href=\"https://doi.org/10.1002/adma.202470004\">https://doi.org/10.1002/adma.202470004</a>.","ista":"Zeng G, Sun Q, Horta S, Wang S, Lu X, Zhang CY, Li J, Li J, Ci L, Tian Y, Ibáñez M, Cabot A. 2024. A layered Bi2Te3@PPy cathode for aqueous Zinc‐Ion batteries: Mechanism and application in printed flexible batteries, Wiley,p.","ieee":"G. Zeng <i>et al.</i>, <i>A layered Bi2Te3@PPy cathode for aqueous Zinc‐Ion batteries: Mechanism and application in printed flexible batteries</i>, vol. 36, no. 1. Wiley, 2024.","short":"G. Zeng, Q. Sun, S. Horta, S. Wang, X. Lu, C.Y. Zhang, J. Li, J. Li, L. Ci, Y. Tian, M. Ibáñez, A. Cabot, A Layered Bi2Te3@PPy Cathode for Aqueous Zinc‐Ion Batteries: Mechanism and Application in Printed Flexible Batteries, Wiley, 2024.","mla":"Zeng, Guifang, et al. “A Layered Bi2Te3@PPy Cathode for Aqueous Zinc‐Ion Batteries: Mechanism and Application in Printed Flexible Batteries.” <i>Advanced Materials</i>, vol. 36, no. 1, 2470004, Wiley, 2024, doi:<a href=\"https://doi.org/10.1002/adma.202470004\">10.1002/adma.202470004</a>.","ama":"Zeng G, Sun Q, Horta S, et al. <i>A Layered Bi2Te3@PPy Cathode for Aqueous Zinc‐Ion Batteries: Mechanism and Application in Printed Flexible Batteries</i>. Vol 36. Wiley; 2024. doi:<a href=\"https://doi.org/10.1002/adma.202470004\">10.1002/adma.202470004</a>","apa":"Zeng, G., Sun, Q., Horta, S., Wang, S., Lu, X., Zhang, C. Y., … Cabot, A. (2024). <i>A layered Bi2Te3@PPy cathode for aqueous Zinc‐Ion batteries: Mechanism and application in printed flexible batteries</i>. <i>Advanced Materials</i> (Vol. 36). Wiley. <a href=\"https://doi.org/10.1002/adma.202470004\">https://doi.org/10.1002/adma.202470004</a>"},"quality_controlled":"1","type":"other_academic_publication","month":"01","oa":1,"publisher":"Wiley","volume":36,"publication_identifier":{"eissn":["1521-4095"],"issn":["0935-9648"]},"intvolume":"        36","OA_place":"publisher","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_number":"2470004","year":"2024","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.1002/adma.202470004"}],"OA_type":"free access","_id":"20057","doi":"10.1002/adma.202470004","issue":"1","author":[{"full_name":"Zeng, Guifang","last_name":"Zeng","first_name":"Guifang"},{"first_name":"Qing","full_name":"Sun, Qing","last_name":"Sun"},{"first_name":"Sharona","full_name":"Horta, Sharona","last_name":"Horta","id":"03a7e858-01b1-11ec-8b71-99ae6c4a05bc"},{"full_name":"Wang, Shang","last_name":"Wang","first_name":"Shang"},{"last_name":"Lu","full_name":"Lu, Xuan","first_name":"Xuan"},{"first_name":"Chao Yue","last_name":"Zhang","full_name":"Zhang, Chao Yue"},{"first_name":"Jing","last_name":"Li","full_name":"Li, Jing"},{"last_name":"Li","full_name":"Li, Junshan","first_name":"Junshan"},{"first_name":"Lijie","full_name":"Ci, Lijie","last_name":"Ci"},{"first_name":"Yanhong","full_name":"Tian, Yanhong","last_name":"Tian"},{"full_name":"Ibáñez, Maria","id":"43C61214-F248-11E8-B48F-1D18A9856A87","last_name":"Ibáñez","orcid":"0000-0001-5013-2843","first_name":"Maria"},{"last_name":"Cabot","full_name":"Cabot, Andreu","first_name":"Andreu"}],"date_created":"2025-07-21T08:53:06Z","department":[{"_id":"MaIb"}]},{"ddc":["570"],"title":"Stuck in uncertainty: A predictive processing/ active inference account of procrastination-like behaviour in autism","abstract":[{"text":"Un fenómeno a menudo asociado con el autismo es un modo atípico de función ejecutiva, cuyas manifestaciones incluyen dificultad para iniciar tareas. En algunos casos, esto va acompañado de sentimientos de inercia y sensaciones que pueden describirse como inquietud y parálisis simultáneas. En consecuencia, la dificultad para iniciar las tareas puede dar lugar a la procrastinación, ya sea simplemente posponiendo el trabajo en la tarea objetivo o realizando otras tareas no relacionadas antes de dedicarse a la tarea objetivo. Curiosamente, sin embargo, también está documentado que, una vez iniciada una tarea, los autistas pueden centrarse en ella intensamente y durante periodos prolongados de tiempo, especialmente cuando les resulta interesante.&#x0D;\r\nEste trabajo utiliza el procesamiento predictivo y la inferencia activa para modelar la relación entre la función ejecutiva, la procrastinación y la hiperfocalización en el autismo. Este modelo integra las causas conocidas y propuestas de los déficits en la función ejecutiva y el papel que desempeña el interés en la regulación de la atención y la motivación. El modelo propone que la procrastinación es el resultado de procesos diferenciales de minimización de errores de predicción, como la ponderación de estímulos sensoriales. Se discuten los vínculos con modelos propuestos previamente, como la coherencia central débil (CCC), y la teoría de los priores altos e inflexibles de los errores de predicción en el autismo (HIPPEA).","lang":"spa"},{"lang":"eng","text":"A  phenomenon  often  associated  with  autism  is  an  atypical  mode  of  executive  function, manifestations  of  which  include  difficulty  in  initiating  tasks.  In  some  cases,  this is accompanied  by  feelings  of  inertia  and  sensations  that  can  be  described  as  simultaneous restlessness  and  paralysis.  Consequently,  difficulty  in  getting  started  on  tasks  can  result  in procrastination,  either  by  simply  postponing  working  on  the  target  task  or  by  performing other  unrelated  tasks  before  engaging  in  the  target  task.  Interestingly,  however,  it  is  also documented  that  once  a  task  has  been  started,  autistic  persons  may  focus  on  it  intensely and for prolonged periods of time, especially when it is interesting to them.This  paper  uses  predictive  processing  and  active  inference  to  model  therelationship between  executive   function,   procrastination,  and   hyperfocus   in  autism.   This   model integrates  the  known  and  proposed  causes  of  deficits  in  executive  function  and  the  role played  by  interest  in  attention  regulation  and  motivation.  The  model  proposes  that procrastination  is  the  outcome  of  differential  prediction-error  minimizing  processes,  such as weighting of sensory stimuli. Links to previously proposed models such as weak central coherence  (WCC),  and  the  theory  of  high,  inflexible  priors  of  prediction  errors  in  autism (HIPPEA) are discussed"}],"publication":"Lógoi. Revista de Filosofía","status":"public","publication_status":"published","date_updated":"2025-09-09T08:51:00Z","day":"19","oa_version":"Published Version","date_published":"2024-03-19T00:00:00Z","article_processing_charge":"Yes","tmp":{"short":"CC BY-NC-SA (4.0)","image":"/images/cc_by_nc_sa.png","name":"Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode"},"oa":1,"publisher":"Universidad Católica Andrés Bello","OA_place":"publisher","publication_identifier":{"issn":["2790-5144"],"eissn":["1316-693X"]},"quality_controlled":"1","month":"03","type":"journal_article","page":"88-114","file":[{"date_updated":"2025-09-09T08:48:53Z","access_level":"open_access","file_size":354124,"relation":"main_file","success":1,"creator":"dernst","date_created":"2025-09-09T08:48:53Z","content_type":"application/pdf","checksum":"04c950f26ad68455c3a303c87ccf2349","file_name":"2025_Logoi_CarlsDiamante.pdf","file_id":"20317"}],"citation":{"ieee":"S. Carls-Diamante and A. Laciny, “Stuck in uncertainty: A predictive processing/ active inference account of procrastination-like behaviour in autism,” <i>Lógoi. Revista de Filosofía</i>, no. 45. Universidad Católica Andrés Bello, pp. 88–114, 2024.","chicago":"Carls-Diamante, Sidney, and Alice Laciny. “Stuck in Uncertainty: A Predictive Processing/ Active Inference Account of Procrastination-like Behaviour in Autism.” <i>Lógoi. Revista de Filosofía</i>. Universidad Católica Andrés Bello, 2024. <a href=\"https://doi.org/10.62876/lr.vi45.6481\">https://doi.org/10.62876/lr.vi45.6481</a>.","ista":"Carls-Diamante S, Laciny A. 2024. Stuck in uncertainty: A predictive processing/ active inference account of procrastination-like behaviour in autism. Lógoi. Revista de Filosofía. (45), 88–114.","mla":"Carls-Diamante, Sidney, and Alice Laciny. “Stuck in Uncertainty: A Predictive Processing/ Active Inference Account of Procrastination-like Behaviour in Autism.” <i>Lógoi. Revista de Filosofía</i>, no. 45, Universidad Católica Andrés Bello, 2024, pp. 88–114, doi:<a href=\"https://doi.org/10.62876/lr.vi45.6481\">10.62876/lr.vi45.6481</a>.","short":"S. Carls-Diamante, A. Laciny, Lógoi. Revista de Filosofía (2024) 88–114.","ama":"Carls-Diamante S, Laciny A. Stuck in uncertainty: A predictive processing/ active inference account of procrastination-like behaviour in autism. <i>Lógoi Revista de Filosofía</i>. 2024;(45):88-114. doi:<a href=\"https://doi.org/10.62876/lr.vi45.6481\">10.62876/lr.vi45.6481</a>","apa":"Carls-Diamante, S., &#38; Laciny, A. (2024). Stuck in uncertainty: A predictive processing/ active inference account of procrastination-like behaviour in autism. <i>Lógoi. Revista de Filosofía</i>. Universidad Católica Andrés Bello. <a href=\"https://doi.org/10.62876/lr.vi45.6481\">https://doi.org/10.62876/lr.vi45.6481</a>"},"article_type":"original","OA_type":"gold","corr_author":"1","file_date_updated":"2025-09-09T08:48:53Z","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2024","PlanS_conform":"1","author":[{"first_name":"Sidney","last_name":"Carls-Diamante","full_name":"Carls-Diamante, Sidney"},{"orcid":"0000-0002-5485-1391","first_name":"Alice","full_name":"Laciny, Alice","id":"accace3f-3f77-11eb-b1df-f1221b04cb95","last_name":"Laciny"}],"date_created":"2025-07-21T10:35:39Z","acknowledgement":"Sidney Carls-Diamante was supported by the Federal Ministry of Education and Research (BMBF) and the Baden-Württemberg Ministry of Science as part of the Excellence Strategy of the German Federal and State Governments. Alice Laciny was supported by the 2021 UNESCO L’Oréal grant for women in science, awarded for the project “Neurodiversity and anthropomorphism in social insect research”.","issue":"45","DOAJ_listed":"1","_id":"20060","doi":"10.62876/lr.vi45.6481","has_accepted_license":"1"},{"title":"PyDaddy: A Python Package for Discovering SDEs from Time Series Data","ddc":["570"],"abstract":[{"text":"PyDaddy is an open source package which is a key contribution of the manuscript Nabeel et al, arXiv:2205.02645. The basic scientific premise for this package is to discover the nature of stochasticity in ecological time series datasets. It is well known that the stochasticity can affect the dynamics of ecological systems in counter-intuitive ways. Without understanding the equations (typically, in the form of stochastic differential equations or SDEs, in short) that govern the dynamics of populations or ecosystems, it's challenging to determine the impact of randomness on real datasets. In this manuscript and accompanying package, we introduce a methodology for discovering equations (SDEs) that transforms time series data of state variables into stochastic differential equations. This approach merges traditional stochastic calculus with modern equation-discovery techniques. We showcase the generality of our method through various applications and discuss its limitations and potential pitfalls, offering diagnostic measures to address these challenges.","lang":"eng"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.5281/zenodo.7137151"}],"status":"public","article_processing_charge":"No","year":"2024","date_published":"2024-09-18T00:00:00Z","related_material":{"record":[{"status":"public","id":"20056","relation":"used_for_analysis_in"}]},"oa_version":"Published Version","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2025-09-30T14:14:42Z","day":"18","tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"oa":1,"publisher":"Zenodo","department":[{"_id":"EdHa"}],"month":"09","type":"research_data_reference","date_created":"2025-08-05T06:49:59Z","author":[{"last_name":"Nabeel","full_name":"Nabeel, Arshed","first_name":"Arshed"},{"first_name":"Ashwin","last_name":"Karichannavar","full_name":"Karichannavar, Ashwin"},{"first_name":"Shuaib","last_name":"Palathingal","full_name":"Palathingal, Shuaib"},{"first_name":"Jitesh","full_name":"Jhawar, Jitesh","last_name":"Jhawar"},{"orcid":"0000-0001-7205-2975","first_name":"David","full_name":"Brückner, David","last_name":"Brückner","id":"e1e86031-6537-11eb-953a-f7ab92be508d"},{"first_name":"Masila","full_name":"Danny Raj, Masila","last_name":"Danny Raj"},{"full_name":"Guttal, Vishwesha","last_name":"Guttal","first_name":"Vishwesha"}],"citation":{"apa":"Nabeel, A., Karichannavar, A., Palathingal, S., Jhawar, J., Brückner, D., Danny Raj, M., &#38; Guttal, V. (2024). PyDaddy: A Python Package for Discovering SDEs from Time Series Data. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.7137151\">https://doi.org/10.5281/ZENODO.7137151</a>","ama":"Nabeel A, Karichannavar A, Palathingal S, et al. PyDaddy: A Python Package for Discovering SDEs from Time Series Data. 2024. doi:<a href=\"https://doi.org/10.5281/ZENODO.7137151\">10.5281/ZENODO.7137151</a>","short":"A. Nabeel, A. Karichannavar, S. Palathingal, J. Jhawar, D. Brückner, M. Danny Raj, V. Guttal, (2024).","mla":"Nabeel, Arshed, et al. <i>PyDaddy: A Python Package for Discovering SDEs from Time Series Data</i>. Zenodo, 2024, doi:<a href=\"https://doi.org/10.5281/ZENODO.7137151\">10.5281/ZENODO.7137151</a>.","chicago":"Nabeel, Arshed, Ashwin Karichannavar, Shuaib Palathingal, Jitesh Jhawar, David Brückner, Masila Danny Raj, and Vishwesha Guttal. “PyDaddy: A Python Package for Discovering SDEs from Time Series Data.” Zenodo, 2024. <a href=\"https://doi.org/10.5281/ZENODO.7137151\">https://doi.org/10.5281/ZENODO.7137151</a>.","ista":"Nabeel A, Karichannavar A, Palathingal S, Jhawar J, Brückner D, Danny Raj M, Guttal V. 2024. PyDaddy: A Python Package for Discovering SDEs from Time Series Data, Zenodo, <a href=\"https://doi.org/10.5281/ZENODO.7137151\">10.5281/ZENODO.7137151</a>.","ieee":"A. Nabeel <i>et al.</i>, “PyDaddy: A Python Package for Discovering SDEs from Time Series Data.” Zenodo, 2024."},"acknowledgement":"This study was partially funded by Science and Engineering Research Board, Department of Science and Technology, Government of India to Vishwesha Guttal.","has_accepted_license":"1","doi":"10.5281/ZENODO.7137151","_id":"20121"},{"citation":{"chicago":"Desrivières, Sylvane, Abigail Miller, Carina M. Mathey, Xinyang Yu, Di Chen, Kofoworola Agunbiade, Stefanie Heilmann-Heimbach, et al. “Multi-Omics Analyses of the EnvironMENTAL Project Provide Insights into Mental Health and Disease.” <i>Nature Mental Health</i>. Springer Nature, 2024. <a href=\"https://doi.org/10.1038/s44220-024-00317-y\">https://doi.org/10.1038/s44220-024-00317-y</a>.","ista":"Desrivières S, Miller A, Mathey CM, Yu X, Chen D, Agunbiade K, Heilmann-Heimbach S, Forstner AJ, Schumann G, Hoffmann P, Nöthen MM, Ogoh G, Stahl B, Young AH, Clinton N, Thompson P, Schwalber A, Liu J, Calhoun V, Chang X, Xia Y, Gong Y, Jia T, Renner P, Hese S, Giner A, Sanchez M, Alvarez E, Spanlang B, Pearmund C, Athanasiadis AP, Otten L, Pitel S, Petkoski S, Jirsa V, Schmitt K, Wilbertz J, Patraskaki M, Sommer P, Claus I, Pastor A, Gallego J, Orosa FE, Viapiana GF, Slater M, Marr L, Novarino G, Marquand A, Böttger SJ, Tschorn M, Rapp M, Ask H, Kjelkenes R, Fernandez S, Van Der Meer D, Westlye LT, Andreassen OA, Aden R, Seefried B, Siehl S, Nees F, Neidhart M, Stringaris A, Schwarz E, Holz N, Tost H, Meyer-Lindenberg A, Christmann N, Jansone K, Banaschewski T, Banks J, Schepanski K, Schütz T, Taron UH, Eils R, Roy JC, Lett TA, Kebir H, Polemiti E, Hitchen E, Jentsch M, Serin E, Bernas A, Vaidya N, Twardziok S, Ralser M, Heinz A, Walter H. 2024. Multi-omics analyses of the environMENTAL project provide insights into mental health and disease. Nature Mental Health. 2(10), 1131–1133.","ieee":"S. Desrivières <i>et al.</i>, “Multi-omics analyses of the environMENTAL project provide insights into mental health and disease,” <i>Nature Mental Health</i>, vol. 2, no. 10. Springer Nature, pp. 1131–1133, 2024.","short":"S. Desrivières, A. Miller, C.M. Mathey, X. Yu, D. Chen, K. Agunbiade, S. Heilmann-Heimbach, A.J. Forstner, G. Schumann, P. Hoffmann, M.M. Nöthen, G. Ogoh, B. Stahl, A.H. Young, N. Clinton, P. Thompson, A. Schwalber, J. Liu, V. Calhoun, X. Chang, Y. Xia, Y. Gong, T. Jia, P. Renner, S. Hese, A. Giner, M. Sanchez, E. Alvarez, B. Spanlang, C. Pearmund, A.P. Athanasiadis, L. Otten, S. Pitel, S. Petkoski, V. Jirsa, K. Schmitt, J. Wilbertz, M. Patraskaki, P. Sommer, I. Claus, A. Pastor, J. Gallego, F.E. Orosa, G.F. Viapiana, M. Slater, L. Marr, G. Novarino, A. Marquand, S.J. Böttger, M. Tschorn, M. Rapp, H. Ask, R. Kjelkenes, S. Fernandez, D. Van Der Meer, L.T. Westlye, O.A. Andreassen, R. Aden, B. Seefried, S. Siehl, F. Nees, M. Neidhart, A. Stringaris, E. Schwarz, N. Holz, H. Tost, A. Meyer-Lindenberg, N. Christmann, K. Jansone, T. Banaschewski, J. Banks, K. Schepanski, T. Schütz, U.H. Taron, R. Eils, J.C. Roy, T.A. Lett, H. Kebir, E. Polemiti, E. Hitchen, M. Jentsch, E. Serin, A. Bernas, N. Vaidya, S. Twardziok, M. Ralser, A. Heinz, H. Walter, Nature Mental Health 2 (2024) 1131–1133.","mla":"Desrivières, Sylvane, et al. “Multi-Omics Analyses of the EnvironMENTAL Project Provide Insights into Mental Health and Disease.” <i>Nature Mental Health</i>, vol. 2, no. 10, Springer Nature, 2024, pp. 1131–33, doi:<a href=\"https://doi.org/10.1038/s44220-024-00317-y\">10.1038/s44220-024-00317-y</a>.","ama":"Desrivières S, Miller A, Mathey CM, et al. Multi-omics analyses of the environMENTAL project provide insights into mental health and disease. <i>Nature Mental Health</i>. 2024;2(10):1131-1133. doi:<a href=\"https://doi.org/10.1038/s44220-024-00317-y\">10.1038/s44220-024-00317-y</a>","apa":"Desrivières, S., Miller, A., Mathey, C. M., Yu, X., Chen, D., Agunbiade, K., … Walter, H. (2024). Multi-omics analyses of the environMENTAL project provide insights into mental health and disease. <i>Nature Mental Health</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s44220-024-00317-y\">https://doi.org/10.1038/s44220-024-00317-y</a>"},"article_type":"comment","publication_identifier":{"eissn":["2731-6076"]},"intvolume":"         2","volume":2,"publisher":"Springer Nature","page":"1131-1133","month":"10","type":"journal_article","quality_controlled":"1","status":"public","publication":"Nature Mental Health","publication_status":"published","date_published":"2024-10-01T00:00:00Z","article_processing_charge":"No","oa_version":"None","day":"01","date_updated":"2025-08-11T06:44:03Z","title":"Multi-omics analyses of the environMENTAL project provide insights into mental health and disease","abstract":[{"lang":"eng","text":"Integrative analyses that incorporate different levels of ‘-omics’ data represent a powerful tool for deciphering the biological mechanisms that underlie environmental influences on mental health and disease. This Comment highlights various aspects of such multi-omics approaches, using the example of the EU-funded environMENTAL project."}],"scopus_import":"1","issue":"10","acknowledgement":"This work was supported by the Horizon 2021 (grant 101057429) and UK Research and Innovation (grants 10038599 and 10041392)-funded project environMENTAL. Other funding included the Medical Research Council and Medical Research Foundation (MR/R00465X/, MRF-058-0004-RG-DESRI, ‘ESTRA’- Neurobiological underpinning of eating disorders: integrative biopsychosocial longitudinal analyses in adolescents; and MR/S020306/1, MRF-058-0009-RG-DESR-C0759 ‘ESTRA’-Establishing causal relationships between biopsychosocial predictors and correlates of eating disorders and their mediation by neural pathways), the EU-funded FP6 Integrated Project IMAGEN (reinforcement-related behavior in normal brain function and psychopathology; LSHM-CT- 2007-037286), the Horizon 2020-funded European Research Council advanced grant for STRATIFY (brain network-based stratification of reinforcement-related disorders; 695313) and the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. This paper represents independent research, partly funded by the NIHR Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. The authors thank C. Schmäl for proofreading the manuscript.","doi":"10.1038/s44220-024-00317-y","_id":"20156","date_created":"2025-08-10T22:01:30Z","department":[{"_id":"GaNo"}],"author":[{"full_name":"Desrivières, Sylvane","last_name":"Desrivières","first_name":"Sylvane"},{"full_name":"Miller, Abigail","last_name":"Miller","first_name":"Abigail"},{"first_name":"Carina M.","full_name":"Mathey, Carina M.","last_name":"Mathey"},{"first_name":"Xinyang","last_name":"Yu","full_name":"Yu, Xinyang"},{"full_name":"Chen, Di","last_name":"Chen","first_name":"Di"},{"last_name":"Agunbiade","full_name":"Agunbiade, Kofoworola","first_name":"Kofoworola"},{"last_name":"Heilmann-Heimbach","full_name":"Heilmann-Heimbach, Stefanie","first_name":"Stefanie"},{"last_name":"Forstner","full_name":"Forstner, Andreas J.","first_name":"Andreas J."},{"last_name":"Schumann","full_name":"Schumann, Gunter","first_name":"Gunter"},{"full_name":"Hoffmann, Per","last_name":"Hoffmann","first_name":"Per"},{"first_name":"Markus M.","full_name":"Nöthen, Markus M.","last_name":"Nöthen"},{"last_name":"Ogoh","full_name":"Ogoh, George","first_name":"George"},{"last_name":"Stahl","full_name":"Stahl, Bernd","first_name":"Bernd"},{"first_name":"Allan H.","full_name":"Young, Allan H.","last_name":"Young"},{"last_name":"Clinton","full_name":"Clinton, Nicholas","first_name":"Nicholas"},{"last_name":"Thompson","full_name":"Thompson, Paul","first_name":"Paul"},{"last_name":"Schwalber","full_name":"Schwalber, Ameli","first_name":"Ameli"},{"first_name":"Jingyu","full_name":"Liu, Jingyu","last_name":"Liu"},{"full_name":"Calhoun, Vince","last_name":"Calhoun","first_name":"Vince"},{"first_name":"Xiao","last_name":"Chang","full_name":"Chang, Xiao"},{"first_name":"Yunman","last_name":"Xia","full_name":"Xia, Yunman"},{"full_name":"Gong, Yanting","last_name":"Gong","first_name":"Yanting"},{"full_name":"Jia, Tianye","last_name":"Jia","first_name":"Tianye"},{"last_name":"Renner","full_name":"Renner, Paul","first_name":"Paul"},{"first_name":"Sören","full_name":"Hese, Sören","last_name":"Hese"},{"last_name":"Giner","full_name":"Giner, Arantxa","first_name":"Arantxa"},{"full_name":"Sanchez, Mavi","last_name":"Sanchez","first_name":"Mavi"},{"full_name":"Alvarez, Elena","last_name":"Alvarez","first_name":"Elena"},{"last_name":"Spanlang","full_name":"Spanlang, Bernhard","first_name":"Bernhard"},{"first_name":"Charlie","last_name":"Pearmund","full_name":"Pearmund, Charlie"},{"first_name":"Anastasios Polykarpos","last_name":"Athanasiadis","full_name":"Athanasiadis, Anastasios Polykarpos"},{"first_name":"Lisa","full_name":"Otten, Lisa","last_name":"Otten"},{"last_name":"Pitel","full_name":"Pitel, Séverine","first_name":"Séverine"},{"last_name":"Petkoski","full_name":"Petkoski, Spase","first_name":"Spase"},{"first_name":"Viktor","last_name":"Jirsa","full_name":"Jirsa, Viktor"},{"last_name":"Schmitt","full_name":"Schmitt, Karen","first_name":"Karen"},{"first_name":"Johannes","last_name":"Wilbertz","full_name":"Wilbertz, Johannes"},{"first_name":"Myrto","last_name":"Patraskaki","full_name":"Patraskaki, Myrto"},{"first_name":"Peter","last_name":"Sommer","full_name":"Sommer, Peter"},{"first_name":"Isabelle","last_name":"Claus","full_name":"Claus, Isabelle"},{"last_name":"Pastor","full_name":"Pastor, Alvaro","first_name":"Alvaro"},{"full_name":"Gallego, Jaime","last_name":"Gallego","first_name":"Jaime"},{"first_name":"Francisco Eiroa","full_name":"Orosa, Francisco Eiroa","last_name":"Orosa"},{"first_name":"Guillem Feixas","last_name":"Viapiana","full_name":"Viapiana, Guillem Feixas"},{"first_name":"Mel","last_name":"Slater","full_name":"Slater, Mel"},{"full_name":"Marr, Lena","id":"4406F586-F248-11E8-B48F-1D18A9856A87","last_name":"Marr","first_name":"Lena"},{"full_name":"Novarino, Gaia","last_name":"Novarino","id":"3E57A680-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-7673-7178","first_name":"Gaia"},{"full_name":"Marquand, Andre","last_name":"Marquand","first_name":"Andre"},{"first_name":"Sarah Jane","last_name":"Böttger","full_name":"Böttger, Sarah Jane"},{"first_name":"Mira","full_name":"Tschorn, Mira","last_name":"Tschorn"},{"full_name":"Rapp, Michael","last_name":"Rapp","first_name":"Michael"},{"full_name":"Ask, Helga","last_name":"Ask","first_name":"Helga"},{"full_name":"Kjelkenes, Rikka","last_name":"Kjelkenes","first_name":"Rikka"},{"full_name":"Fernandez, Sara","last_name":"Fernandez","first_name":"Sara"},{"full_name":"Van Der Meer, Dennis","last_name":"Van Der Meer","first_name":"Dennis"},{"first_name":"Lars T.","last_name":"Westlye","full_name":"Westlye, Lars T."},{"full_name":"Andreassen, Ole A.","last_name":"Andreassen","first_name":"Ole A."},{"last_name":"Aden","full_name":"Aden, Rieke","first_name":"Rieke"},{"full_name":"Seefried, Beke","last_name":"Seefried","first_name":"Beke"},{"first_name":"Sebastian","last_name":"Siehl","full_name":"Siehl, Sebastian"},{"first_name":"Frauke","last_name":"Nees","full_name":"Nees, Frauke"},{"first_name":"Maja","full_name":"Neidhart, Maja","last_name":"Neidhart"},{"first_name":"Argyris","full_name":"Stringaris, Argyris","last_name":"Stringaris"},{"full_name":"Schwarz, Emanuel","last_name":"Schwarz","first_name":"Emanuel"},{"full_name":"Holz, Nathalie","last_name":"Holz","first_name":"Nathalie"},{"first_name":"Heike","full_name":"Tost, Heike","last_name":"Tost"},{"full_name":"Meyer-Lindenberg, Andreas","last_name":"Meyer-Lindenberg","first_name":"Andreas"},{"last_name":"Christmann","full_name":"Christmann, Nina","first_name":"Nina"},{"first_name":"Karina","last_name":"Jansone","full_name":"Jansone, Karina"},{"first_name":"Tobias","last_name":"Banaschewski","full_name":"Banaschewski, Tobias"},{"first_name":"Jamie","full_name":"Banks, Jamie","last_name":"Banks"},{"full_name":"Schepanski, Kerstin","last_name":"Schepanski","first_name":"Kerstin"},{"first_name":"Tatjana","full_name":"Schütz, Tatjana","last_name":"Schütz"},{"last_name":"Taron","full_name":"Taron, Ulrike Helene","first_name":"Ulrike Helene"},{"last_name":"Eils","full_name":"Eils, Roland","first_name":"Roland"},{"first_name":"Jean Charles","last_name":"Roy","full_name":"Roy, Jean Charles"},{"last_name":"Lett","full_name":"Lett, Tristram A.","first_name":"Tristram A."},{"last_name":"Kebir","full_name":"Kebir, Hedi","first_name":"Hedi"},{"full_name":"Polemiti, Elli","last_name":"Polemiti","first_name":"Elli"},{"last_name":"Hitchen","full_name":"Hitchen, Esther","first_name":"Esther"},{"full_name":"Jentsch, Marcel","last_name":"Jentsch","first_name":"Marcel"},{"last_name":"Serin","full_name":"Serin, Emin","first_name":"Emin"},{"first_name":"Antoine","full_name":"Bernas, Antoine","last_name":"Bernas"},{"full_name":"Vaidya, Nilakshi","last_name":"Vaidya","first_name":"Nilakshi"},{"first_name":"Sven","last_name":"Twardziok","full_name":"Twardziok, Sven"},{"last_name":"Ralser","full_name":"Ralser, Markus","first_name":"Markus"},{"full_name":"Heinz, Andreas","last_name":"Heinz","first_name":"Andreas"},{"full_name":"Walter, Henrik","last_name":"Walter","first_name":"Henrik"}],"year":"2024","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","OA_type":"closed access","language":[{"iso":"eng"}]},{"year":"2024","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_number":"1128-1130","language":[{"iso":"eng"}],"OA_type":"closed access","doi":"10.1038/s44220-024-00320-3","_id":"20157","scopus_import":"1","issue":"10","acknowledgement":"Funded provided by the European Union. Complementary funding was received by UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee (10131373and 10038599) and Ministry of Science and Technology of China (MOST) National Key Project of ‘Inter-governmental International Scientific and Technological Innovation Cooperation’ (2023YFE0199700).","department":[{"_id":"GaNo"}],"date_created":"2025-08-10T22:01:30Z","author":[{"first_name":"Bernd","full_name":"Stahl, Bernd","last_name":"Stahl"},{"full_name":"Ogoh, George","last_name":"Ogoh","first_name":"George"},{"first_name":"Gunter","full_name":"Schumann, Gunter","last_name":"Schumann"},{"full_name":"Walter, Henrik","last_name":"Walter","first_name":"Henrik"},{"last_name":"Stahl","full_name":"Stahl, Bernd","first_name":"Bernd"},{"first_name":"Allan H.","last_name":"Young","full_name":"Young, Allan H."},{"full_name":"Desrivières, Sylvane","last_name":"Desrivières","first_name":"Sylvane"},{"last_name":"Clinton","full_name":"Clinton, Nicholas","first_name":"Nicholas"},{"full_name":"Thompson, Paul","last_name":"Thompson","first_name":"Paul"},{"first_name":"Ameli","full_name":"Schwalber, Ameli","last_name":"Schwalber"},{"first_name":"Jingyu","full_name":"Liu, Jingyu","last_name":"Liu"},{"first_name":"Vince","last_name":"Calhoun","full_name":"Calhoun, Vince"},{"last_name":"Chang","full_name":"Chang, Xiao","first_name":"Xiao"},{"first_name":"Yunman","last_name":"Xia","full_name":"Xia, Yunman"},{"first_name":"Yanting","full_name":"Gong, Yanting","last_name":"Gong"},{"full_name":"Jia, Tianye","last_name":"Jia","first_name":"Tianye"},{"first_name":"Paul","last_name":"Renner","full_name":"Renner, Paul"},{"first_name":"Sören","last_name":"Hese","full_name":"Hese, Sören"},{"full_name":"Giner, Arantxa","last_name":"Giner","first_name":"Arantxa"},{"first_name":"Mavi","full_name":"Sanchez, Mavi","last_name":"Sanchez"},{"full_name":"Alvarez, Elena","last_name":"Alvarez","first_name":"Elena"},{"first_name":"Bernhard","full_name":"Spanlang, Bernhard","last_name":"Spanlang"},{"last_name":"Pearmund","full_name":"Pearmund, Charlie","first_name":"Charlie"},{"first_name":"Anastasios Polykarpos","last_name":"Athanasiadis","full_name":"Athanasiadis, Anastasios Polykarpos"},{"last_name":"Otten","full_name":"Otten, Lisa","first_name":"Lisa"},{"full_name":"Pitel, Séverine","last_name":"Pitel","first_name":"Séverine"},{"last_name":"Petkoski","full_name":"Petkoski, Spase","first_name":"Spase"},{"full_name":"Jirsa, Viktor","last_name":"Jirsa","first_name":"Viktor"},{"last_name":"Schmitt","full_name":"Schmitt, Karen","first_name":"Karen"},{"first_name":"Johannes","full_name":"Wilbertz, Johannes","last_name":"Wilbertz"},{"first_name":"Myrto","last_name":"Patraskaki","full_name":"Patraskaki, Myrto"},{"first_name":"Peter","full_name":"Sommer, Peter","last_name":"Sommer"},{"first_name":"Stefanie","last_name":"Heilmann-Heimbach","full_name":"Heilmann-Heimbach, Stefanie"},{"first_name":"Carina M.","last_name":"Mathey","full_name":"Mathey, Carina M."},{"first_name":"Abigail","full_name":"Miller, Abigail","last_name":"Miller"},{"first_name":"Isabelle","full_name":"Claus, Isabelle","last_name":"Claus"},{"first_name":"Markus M.","full_name":"Nöthen, Markus M.","last_name":"Nöthen"},{"first_name":"Per","last_name":"Hoffmann","full_name":"Hoffmann, Per"},{"first_name":"Andreas J.","full_name":"Forstner, Andreas J.","last_name":"Forstner"},{"last_name":"Pastor","full_name":"Pastor, Alvaro","first_name":"Alvaro"},{"full_name":"Gallego, Jaime","last_name":"Gallego","first_name":"Jaime"},{"full_name":"Orosa, Francisco Eiroa","last_name":"Orosa","first_name":"Francisco Eiroa"},{"full_name":"Viapiana, Guillem Feixas","last_name":"Viapiana","first_name":"Guillem Feixas"},{"first_name":"Mel","last_name":"Slater","full_name":"Slater, Mel"},{"first_name":"Lena","id":"4406F586-F248-11E8-B48F-1D18A9856A87","last_name":"Marr","full_name":"Marr, Lena"},{"orcid":"0000-0002-7673-7178","first_name":"Gaia","full_name":"Novarino, Gaia","last_name":"Novarino","id":"3E57A680-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Andre","last_name":"Marquand","full_name":"Marquand, Andre"},{"full_name":"Böttger, Sarah Jane","last_name":"Böttger","first_name":"Sarah Jane"},{"first_name":"Mira","full_name":"Tschorn, Mira","last_name":"Tschorn"},{"first_name":"Michael","full_name":"Rapp, Michael","last_name":"Rapp"},{"first_name":"Helga","full_name":"Ask, Helga","last_name":"Ask"},{"full_name":"Kjelkenes, Rikka","last_name":"Kjelkenes","first_name":"Rikka"},{"first_name":"Sara","last_name":"Fernandez","full_name":"Fernandez, Sara"},{"full_name":"Van Der Meer, Dennis","last_name":"Van Der Meer","first_name":"Dennis"},{"last_name":"Westlye","full_name":"Westlye, Lars T.","first_name":"Lars T."},{"first_name":"Ole A.","last_name":"Andreassen","full_name":"Andreassen, Ole A."},{"full_name":"Aden, Rieke","last_name":"Aden","first_name":"Rieke"},{"first_name":"Beke","full_name":"Seefried, Beke","last_name":"Seefried"},{"full_name":"Siehl, Sebastian","last_name":"Siehl","first_name":"Sebastian"},{"full_name":"Nees, Frauke","last_name":"Nees","first_name":"Frauke"},{"first_name":"Maja","full_name":"Neidhart, Maja","last_name":"Neidhart"},{"last_name":"Stringaris","full_name":"Stringaris, Argyris","first_name":"Argyris"},{"full_name":"Schwarz, Emanuel","last_name":"Schwarz","first_name":"Emanuel"},{"last_name":"Holz","full_name":"Holz, Nathalie","first_name":"Nathalie"},{"first_name":"Heike","full_name":"Tost, Heike","last_name":"Tost"},{"last_name":"Meyer-Lindenberg","full_name":"Meyer-Lindenberg, Andreas","first_name":"Andreas"},{"first_name":"Nina","full_name":"Christmann, Nina","last_name":"Christmann"},{"full_name":"Jansone, Karina","last_name":"Jansone","first_name":"Karina"},{"full_name":"Banaschewski, Tobias","last_name":"Banaschewski","first_name":"Tobias"},{"first_name":"Jamie","last_name":"Banks","full_name":"Banks, Jamie"},{"first_name":"Kerstin","full_name":"Schepanski, Kerstin","last_name":"Schepanski"},{"last_name":"Schütz","full_name":"Schütz, Tatjana","first_name":"Tatjana"},{"last_name":"Taron","full_name":"Taron, Ulrike Helene","first_name":"Ulrike Helene"},{"first_name":"Roland","last_name":"Eils","full_name":"Eils, Roland"},{"last_name":"Roy","full_name":"Roy, Jean Charles","first_name":"Jean Charles"},{"last_name":"Lett","full_name":"Lett, Tristram A.","first_name":"Tristram A."},{"first_name":"Hedi","last_name":"Kebir","full_name":"Kebir, Hedi"},{"first_name":"Elli","full_name":"Polemiti, Elli","last_name":"Polemiti"},{"first_name":"Esther","full_name":"Hitchen, Esther","last_name":"Hitchen"},{"full_name":"Jentsch, Marcel","last_name":"Jentsch","first_name":"Marcel"},{"first_name":"Emin","last_name":"Serin","full_name":"Serin, Emin"},{"first_name":"Antoine","full_name":"Bernas, Antoine","last_name":"Bernas"},{"first_name":"Nilakshi","last_name":"Vaidya","full_name":"Vaidya, Nilakshi"},{"full_name":"Twardziok, Sven","last_name":"Twardziok","first_name":"Sven"},{"first_name":"Markus","full_name":"Ralser, Markus","last_name":"Ralser"},{"last_name":"Heinz","full_name":"Heinz, Andreas","first_name":"Andreas"},{"first_name":"Henrik","last_name":"Walter","full_name":"Walter, Henrik"}],"date_published":"2024-10-01T00:00:00Z","article_processing_charge":"No","oa_version":"None","day":"01","date_updated":"2025-08-11T06:53:55Z","publication_status":"published","status":"public","publication":"Nature Mental Health","abstract":[{"text":"The focus of much of contemporary research ethics is on compliance with established protocols. However, large data-driven neuroscience research raises new ethical concerns that have no agreed-upon solution. Here we reflect on these challenges and propose better integration of public and patient involvement in this evolving landscape.","lang":"eng"}],"title":"Rethinking ethics in interdisciplinary and big data-driven neuroscience projects","article_type":"comment","citation":{"apa":"Stahl, B., Ogoh, G., Schumann, G., Walter, H., Stahl, B., Young, A. H., … Walter, H. (2024). Rethinking ethics in interdisciplinary and big data-driven neuroscience projects. <i>Nature Mental Health</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s44220-024-00320-3\">https://doi.org/10.1038/s44220-024-00320-3</a>","ama":"Stahl B, Ogoh G, Schumann G, et al. Rethinking ethics in interdisciplinary and big data-driven neuroscience projects. <i>Nature Mental Health</i>. 2024;2(10). doi:<a href=\"https://doi.org/10.1038/s44220-024-00320-3\">10.1038/s44220-024-00320-3</a>","short":"B. Stahl, G. Ogoh, G. Schumann, H. Walter, B. Stahl, A.H. Young, S. Desrivières, N. Clinton, P. Thompson, A. Schwalber, J. Liu, V. Calhoun, X. Chang, Y. Xia, Y. Gong, T. Jia, P. Renner, S. Hese, A. Giner, M. Sanchez, E. Alvarez, B. Spanlang, C. Pearmund, A.P. Athanasiadis, L. Otten, S. Pitel, S. Petkoski, V. Jirsa, K. Schmitt, J. Wilbertz, M. Patraskaki, P. Sommer, S. Heilmann-Heimbach, C.M. Mathey, A. Miller, I. Claus, M.M. Nöthen, P. Hoffmann, A.J. Forstner, A. Pastor, J. Gallego, F.E. Orosa, G.F. Viapiana, M. Slater, L. Marr, G. Novarino, A. Marquand, S.J. Böttger, M. Tschorn, M. Rapp, H. Ask, R. Kjelkenes, S. Fernandez, D. Van Der Meer, L.T. Westlye, O.A. Andreassen, R. Aden, B. Seefried, S. Siehl, F. Nees, M. Neidhart, A. Stringaris, E. Schwarz, N. Holz, H. Tost, A. Meyer-Lindenberg, N. Christmann, K. Jansone, T. Banaschewski, J. Banks, K. Schepanski, T. Schütz, U.H. Taron, R. Eils, J.C. Roy, T.A. Lett, H. Kebir, E. Polemiti, E. Hitchen, M. Jentsch, E. Serin, A. Bernas, N. Vaidya, S. Twardziok, M. Ralser, A. Heinz, H. Walter, Nature Mental Health 2 (2024).","mla":"Stahl, Bernd, et al. “Rethinking Ethics in Interdisciplinary and Big Data-Driven Neuroscience Projects.” <i>Nature Mental Health</i>, vol. 2, no. 10, 1128–1130, Springer Nature, 2024, doi:<a href=\"https://doi.org/10.1038/s44220-024-00320-3\">10.1038/s44220-024-00320-3</a>.","chicago":"Stahl, Bernd, George Ogoh, Gunter Schumann, Henrik Walter, Bernd Stahl, Allan H. Young, Sylvane Desrivières, et al. “Rethinking Ethics in Interdisciplinary and Big Data-Driven Neuroscience Projects.” <i>Nature Mental Health</i>. Springer Nature, 2024. <a href=\"https://doi.org/10.1038/s44220-024-00320-3\">https://doi.org/10.1038/s44220-024-00320-3</a>.","ista":"Stahl B, Ogoh G, Schumann G, Walter H, Stahl B, Young AH, Desrivières S, Clinton N, Thompson P, Schwalber A, Liu J, Calhoun V, Chang X, Xia Y, Gong Y, Jia T, Renner P, Hese S, Giner A, Sanchez M, Alvarez E, Spanlang B, Pearmund C, Athanasiadis AP, Otten L, Pitel S, Petkoski S, Jirsa V, Schmitt K, Wilbertz J, Patraskaki M, Sommer P, Heilmann-Heimbach S, Mathey CM, Miller A, Claus I, Nöthen MM, Hoffmann P, Forstner AJ, Pastor A, Gallego J, Orosa FE, Viapiana GF, Slater M, Marr L, Novarino G, Marquand A, Böttger SJ, Tschorn M, Rapp M, Ask H, Kjelkenes R, Fernandez S, Van Der Meer D, Westlye LT, Andreassen OA, Aden R, Seefried B, Siehl S, Nees F, Neidhart M, Stringaris A, Schwarz E, Holz N, Tost H, Meyer-Lindenberg A, Christmann N, Jansone K, Banaschewski T, Banks J, Schepanski K, Schütz T, Taron UH, Eils R, Roy JC, Lett TA, Kebir H, Polemiti E, Hitchen E, Jentsch M, Serin E, Bernas A, Vaidya N, Twardziok S, Ralser M, Heinz A, Walter H. 2024. Rethinking ethics in interdisciplinary and big data-driven neuroscience projects. Nature Mental Health. 2(10), 1128–1130.","ieee":"B. Stahl <i>et al.</i>, “Rethinking ethics in interdisciplinary and big data-driven neuroscience projects,” <i>Nature Mental Health</i>, vol. 2, no. 10. Springer Nature, 2024."},"month":"10","type":"journal_article","quality_controlled":"1","publication_identifier":{"eissn":["2731-6076"]},"intvolume":"         2","publisher":"Springer Nature","volume":2},{"title":"Questioning claims of monitoring the Michael addition reaction at the single-molecule level","abstract":[{"lang":"eng","text":"Arising from C. Yang et al. Nature Chemistry https://doi.org/10.1038/s41557-023-01212-2 (2023)\r\n\r\nIn this work Yang et al.1 claim that an enantioselective Michael addition reaction with a barrier of 16 kcal mol−1 occurs at the single-molecule level in frozen solvent by measuring fluctuations in current flowing across graphene-based molecular devices. The article, however, contains major scientific errors that undermine their conclusions. We highlight issues with the fabrication of the devices, a lack of characterization, discrepancies between theory and experiment, unreliable inelastic electron tunnelling spectra (IETS) and a perceived misinterpretation of noise as evidence of reaction."}],"status":"public","publication":"Nature Chemistry","publication_status":"published","date_updated":"2025-10-23T12:58:52Z","day":"01","oa_version":"None","date_published":"2024-11-01T00:00:00Z","article_processing_charge":"No","publisher":"Springer Nature","volume":16,"intvolume":"        16","publication_identifier":{"eissn":["1755-4349"],"issn":["1755-4330"]},"extern":"1","quality_controlled":"1","month":"11","type":"journal_article","external_id":{"pmid":["39313629"]},"page":"1767-1769","pmid":1,"citation":{"ama":"Venkataraman L, van Ruitenbeek J. Questioning claims of monitoring the Michael addition reaction at the single-molecule level. <i>Nature Chemistry</i>. 2024;16(11):1767-1769. doi:<a href=\"https://doi.org/10.1038/s41557-024-01631-9\">10.1038/s41557-024-01631-9</a>","apa":"Venkataraman, L., &#38; van Ruitenbeek, J. (2024). Questioning claims of monitoring the Michael addition reaction at the single-molecule level. <i>Nature Chemistry</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41557-024-01631-9\">https://doi.org/10.1038/s41557-024-01631-9</a>","ieee":"L. Venkataraman and J. van Ruitenbeek, “Questioning claims of monitoring the Michael addition reaction at the single-molecule level,” <i>Nature Chemistry</i>, vol. 16, no. 11. Springer Nature, pp. 1767–1769, 2024.","chicago":"Venkataraman, Latha, and Jan van Ruitenbeek. “Questioning Claims of Monitoring the Michael Addition Reaction at the Single-Molecule Level.” <i>Nature Chemistry</i>. Springer Nature, 2024. <a href=\"https://doi.org/10.1038/s41557-024-01631-9\">https://doi.org/10.1038/s41557-024-01631-9</a>.","ista":"Venkataraman L, van Ruitenbeek J. 2024. Questioning claims of monitoring the Michael addition reaction at the single-molecule level. Nature Chemistry. 16(11), 1767–1769.","mla":"Venkataraman, Latha, and Jan van Ruitenbeek. “Questioning Claims of Monitoring the Michael Addition Reaction at the Single-Molecule Level.” <i>Nature Chemistry</i>, vol. 16, no. 11, Springer Nature, 2024, pp. 1767–69, doi:<a href=\"https://doi.org/10.1038/s41557-024-01631-9\">10.1038/s41557-024-01631-9</a>.","short":"L. Venkataraman, J. van Ruitenbeek, Nature Chemistry 16 (2024) 1767–1769."},"article_type":"letter_note","OA_type":"closed access","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2024","author":[{"orcid":"0000-0002-6957-6089","first_name":"Latha","full_name":"Venkataraman, Latha","id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","last_name":"Venkataraman"},{"first_name":"Jan","last_name":"van Ruitenbeek","full_name":"van Ruitenbeek, Jan"}],"date_created":"2025-10-23T12:16:57Z","issue":"11","scopus_import":"1","_id":"20527","doi":"10.1038/s41557-024-01631-9"},{"abstract":[{"lang":"eng","text":"Single molecules bridging two metallic electrodes can emit light through electroluminescence when subjected to a bias voltage. Typically, light emission in such devices results from transitions between molecular states, although in the presence of light-matter coupling, the emission can result from a transition between hybrid light-matter states. Here, we create single metal-molecule-metal junctions and simultaneously collect conductance and electroluminescence data using a scanning tunneling microscope (STM) equipped with a custom spectrometer. Through experimental analysis and electronic structure calculations, we provide evidence for a molecule-electrode interfacial exciton coupled to a junction cavity plasmon. Importantly, we find that close to resonant transport conditions, the molecular junction functions as a single emitter that is strongly coupled to the junction cavity mode, leading to characteristic Rabi splitting of the emission spectrum and providing the first example of an electroluminescence-driven single-molecule system in the regime of strong light-matter coupling."}],"title":"Plasmon-exciton strong coupling in single-molecule junction electroluminescence","article_processing_charge":"No","date_published":"2024-12-04T00:00:00Z","oa_version":"None","day":"04","date_updated":"2025-10-23T13:03:41Z","publication":"Journal of the American Chemical Society","publication_status":"published","status":"public","page":"34394-34400","type":"journal_article","external_id":{"pmid":["39630979"]},"month":"12","quality_controlled":"1","extern":"1","publication_identifier":{"issn":["0002-7863"],"eissn":["1520-5126"]},"intvolume":"       146","volume":146,"publisher":"American Chemical Society","article_type":"original","pmid":1,"citation":{"ama":"Paoletta AL, Hoffmann NM, Cheng DW, et al. Plasmon-exciton strong coupling in single-molecule junction electroluminescence. <i>Journal of the American Chemical Society</i>. 2024;146(50):34394-34400. doi:<a href=\"https://doi.org/10.1021/jacs.4c09782\">10.1021/jacs.4c09782</a>","apa":"Paoletta, A. L., Hoffmann, N. M., Cheng, D. W., York, E., Xu, D., Zhang, B., … Venkataraman, L. (2024). Plasmon-exciton strong coupling in single-molecule junction electroluminescence. <i>Journal of the American Chemical Society</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/jacs.4c09782\">https://doi.org/10.1021/jacs.4c09782</a>","ista":"Paoletta AL, Hoffmann NM, Cheng DW, York E, Xu D, Zhang B, Delor M, Berkelbach TC, Venkataraman L. 2024. Plasmon-exciton strong coupling in single-molecule junction electroluminescence. Journal of the American Chemical Society. 146(50), 34394–34400.","chicago":"Paoletta, Angela L., Norah M. Hoffmann, Daniel W. Cheng, Emma York, Ding Xu, Boyuan Zhang, Milan Delor, Timothy C. Berkelbach, and Latha Venkataraman. “Plasmon-Exciton Strong Coupling in Single-Molecule Junction Electroluminescence.” <i>Journal of the American Chemical Society</i>. American Chemical Society, 2024. <a href=\"https://doi.org/10.1021/jacs.4c09782\">https://doi.org/10.1021/jacs.4c09782</a>.","ieee":"A. L. Paoletta <i>et al.</i>, “Plasmon-exciton strong coupling in single-molecule junction electroluminescence,” <i>Journal of the American Chemical Society</i>, vol. 146, no. 50. American Chemical Society, pp. 34394–34400, 2024.","short":"A.L. Paoletta, N.M. Hoffmann, D.W. Cheng, E. York, D. Xu, B. Zhang, M. Delor, T.C. Berkelbach, L. Venkataraman, Journal of the American Chemical Society 146 (2024) 34394–34400.","mla":"Paoletta, Angela L., et al. “Plasmon-Exciton Strong Coupling in Single-Molecule Junction Electroluminescence.” <i>Journal of the American Chemical Society</i>, vol. 146, no. 50, American Chemical Society, 2024, pp. 34394–400, doi:<a href=\"https://doi.org/10.1021/jacs.4c09782\">10.1021/jacs.4c09782</a>."},"language":[{"iso":"eng"}],"OA_type":"closed access","year":"2024","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_created":"2025-10-23T12:20:19Z","author":[{"full_name":"Paoletta, Angela L.","last_name":"Paoletta","first_name":"Angela L."},{"full_name":"Hoffmann, Norah M.","last_name":"Hoffmann","first_name":"Norah M."},{"full_name":"Cheng, Daniel W.","last_name":"Cheng","first_name":"Daniel W."},{"first_name":"Emma","full_name":"York, Emma","last_name":"York"},{"full_name":"Xu, Ding","last_name":"Xu","first_name":"Ding"},{"last_name":"Zhang","full_name":"Zhang, Boyuan","first_name":"Boyuan"},{"first_name":"Milan","full_name":"Delor, Milan","last_name":"Delor"},{"full_name":"Berkelbach, Timothy C.","last_name":"Berkelbach","first_name":"Timothy C."},{"first_name":"Latha","orcid":"0000-0002-6957-6089","id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","last_name":"Venkataraman","full_name":"Venkataraman, Latha"}],"doi":"10.1021/jacs.4c09782","_id":"20529","scopus_import":"1","issue":"50"}]