[{"article_number":"2406.04102","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)"},"date_updated":"2025-02-10T08:14:27Z","_id":"18999","date_created":"2025-02-04T16:21:21Z","status":"public","department":[{"_id":"GradSch"},{"_id":"HeEd"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2406.04102"}],"citation":{"short":"S. Cultrera di Montesano, O. Draganov, H. Edelsbrunner, M. Saghafian, ArXiv (n.d.).","chicago":"Cultrera di Montesano, Sebastiano, Ondrej Draganov, Herbert Edelsbrunner, and Morteza Saghafian. “Chromatic Topological Data Analysis.” ArXiv, n.d. https://doi.org/10.48550/ARXIV.2406.04102.","apa":"Cultrera di Montesano, S., Draganov, O., Edelsbrunner, H., & Saghafian, M. (n.d.). Chromatic topological data analysis. arXiv. https://doi.org/10.48550/ARXIV.2406.04102","ieee":"S. Cultrera di Montesano, O. Draganov, H. Edelsbrunner, and M. Saghafian, “Chromatic topological data analysis,” arXiv. .","mla":"Cultrera di Montesano, Sebastiano, et al. “Chromatic Topological Data Analysis.” ArXiv, 2406.04102, doi:10.48550/ARXIV.2406.04102.","ista":"Cultrera di Montesano S, Draganov O, Edelsbrunner H, Saghafian M. Chromatic topological data analysis. arXiv, 2406.04102.","ama":"Cultrera di Montesano S, Draganov O, Edelsbrunner H, Saghafian M. Chromatic topological data analysis. arXiv. doi:10.48550/ARXIV.2406.04102"},"language":[{"iso":"eng"}],"oa_version":"Preprint","title":"Chromatic topological data analysis","doi":"10.48550/ARXIV.2406.04102","publication_status":"submitted","date_published":"2024-06-06T00:00:00Z","author":[{"last_name":"Cultrera di Montesano","orcid":"0000-0001-6249-0832","id":"34D2A09C-F248-11E8-B48F-1D18A9856A87","first_name":"Sebastiano","full_name":"Cultrera di Montesano, Sebastiano"},{"last_name":"Draganov","orcid":"0000-0003-0464-3823","id":"2B23F01E-F248-11E8-B48F-1D18A9856A87","first_name":"Ondrej","full_name":"Draganov, Ondrej"},{"orcid":"0000-0002-9823-6833","last_name":"Edelsbrunner","id":"3FB178DA-F248-11E8-B48F-1D18A9856A87","first_name":"Herbert","full_name":"Edelsbrunner, Herbert"},{"full_name":"Saghafian, Morteza","last_name":"Saghafian","id":"f86f7148-b140-11ec-9577-95435b8df824","first_name":"Morteza"}],"OA_type":"green","day":"06","abstract":[{"lang":"eng","text":"Exploring the shape of point configurations has been a key driver in the evolution of TDA (short for topological data analysis) since its infancy. This survey illustrates the recent efforts to broaden these ideas to model spatial interactions among multiple configurations, each distinguished by a color. It describes advances in this area and prepares the ground for further exploration by mentioning unresolved questions and promising research avenues while focusing on the overlap with discrete geometry."}],"corr_author":"1","ddc":["510"],"has_accepted_license":"1","OA_place":"repository","publication":"arXiv","external_id":{"arxiv":["2406.04102"]},"oa":1,"article_processing_charge":"No","arxiv":1,"month":"06","type":"preprint","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","license":"https://creativecommons.org/licenses/by/4.0/","fulldoi":"https://doi.org/10.48550/ARXIV.2406.04102","year":"2024"},{"month":"12","oa":1,"article_processing_charge":"Yes (in subscription journal)","OA_place":"publisher","publication":"Proceedings - SIGGRAPH Asia 2024 Conference Papers","external_id":{"isi":["001441591200068"]},"acknowledgement":"We would like to thank Lukas Lipp for fruitful discussions, Károly Zsolnai-Fehér and Jaroslav Křivánek for valuable contributions to early versions of this work, and Bernhard Kerbl for help with our CUDA implementation. Moreover, we would like to thank the creators of the scenes we have used: Wig42 for “Wooden Staircase” (Fig. 1), “Grey and White Room” (Fig. S6), and “Modern Living Room” (Fig. S8); nacimus for “Bathroom” (Fig. 3, S5); NovaZeeke for “Japanese Classroom” (Fig. 4, 6); Beeple for “Zero-Day” (Fig. 8); Jay-Artist for “White Room” (Fig. S7); Mareck for “Contemporary Bathroom” (Fig. 2); Christian Freude for “Glass Caustics” (Fig. S10); and Benedikt Bitterli for “Veach Ajar” (Fig. 7, S2), “Veach MIS” (Fig. S4), and “Fur Ball” (Fig. S11). This work has received funding from the Vienna Science and Technology Fund (WWTF) project ICT22-028 (“Toward Optimal Path Guiding for Photorealistic Rendering”) and the Austrian Science Fund (FWF) project F 77 (SFB “Advanced Computational Design”).","has_accepted_license":"1","ddc":["000"],"publisher":"Association for Computing Machinery","publication_identifier":{"isbn":["9798400711312"]},"abstract":[{"text":"The stochastic nature of modern Monte Carlo (MC) rendering methods inevitably produces noise in rendered images for a practical number of samples per pixel. The problem of denoising these images has been widely studied, with most recent methods relying on data-driven, pretrained neural networks. In contrast, in this paper we propose a statistical approach to the denoising problem, treating each pixel as a random variable and reasoning about its distribution. Considering a pixel of the noisy rendered image, we formulate fast pair-wise statistical tests—based on online estimators—to decide which of the nearby pixels to exclude from the denoising filter. We show that for symmetric pixel weights and normally distributed samples, the classical Welch t-test is optimal in terms of mean squared error. We then show how to extend this result to handle non-normal distributions, using more recent confidence-interval formulations in combination with the Box-Cox transformation. Our results show that our statistical denoising approach matches the performance of state-of-the-art neural image denoising without having to resort to any computation-intensive pretraining. Furthermore, our approach easily generalizes to other quantities besides pixel intensity, which we demonstrate by showing additional applications to Russian roulette path termination and multiple importance sampling.","lang":"eng"}],"scopus_import":"1","day":"03","fulldoi":"https://doi.org/10.1145/3680528.3687591","conference":{"start_date":"2024-12-03","end_date":"2024-12-06","name":"SA: SIGGRAPH Asia","location":"Tokyo, Japan"},"year":"2024","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"conference","oa_version":"Published Version","language":[{"iso":"eng"}],"citation":{"apa":"Sakai, H., Freude, C., Auzinger, T., Hahn, D., & Wimmer, M. (2024). A statistical approach to Monte Carlo denoising. In Proceedings - SIGGRAPH Asia 2024 Conference Papers. Tokyo, Japan: Association for Computing Machinery. https://doi.org/10.1145/3680528.3687591","chicago":"Sakai, Hiroyuki, Christian Freude, Thomas Auzinger, David Hahn, and Michael Wimmer. “A Statistical Approach to Monte Carlo Denoising.” In Proceedings - SIGGRAPH Asia 2024 Conference Papers. Association for Computing Machinery, 2024. https://doi.org/10.1145/3680528.3687591.","short":"H. Sakai, C. Freude, T. Auzinger, D. Hahn, M. Wimmer, in:, Proceedings - SIGGRAPH Asia 2024 Conference Papers, Association for Computing Machinery, 2024.","ama":"Sakai H, Freude C, Auzinger T, Hahn D, Wimmer M. A statistical approach to Monte Carlo denoising. In: Proceedings - SIGGRAPH Asia 2024 Conference Papers. Association for Computing Machinery; 2024. doi:10.1145/3680528.3687591","ista":"Sakai H, Freude C, Auzinger T, Hahn D, Wimmer M. 2024. A statistical approach to Monte Carlo denoising. Proceedings - SIGGRAPH Asia 2024 Conference Papers. SA: SIGGRAPH Asia, 68.","mla":"Sakai, Hiroyuki, et al. “A Statistical Approach to Monte Carlo Denoising.” Proceedings - SIGGRAPH Asia 2024 Conference Papers, 68, Association for Computing Machinery, 2024, doi:10.1145/3680528.3687591.","ieee":"H. Sakai, C. Freude, T. Auzinger, D. Hahn, and M. Wimmer, “A statistical approach to Monte Carlo denoising,” in Proceedings - SIGGRAPH Asia 2024 Conference Papers, Tokyo, Japan, 2024."},"status":"public","date_created":"2025-02-16T23:02:34Z","quality_controlled":"1","article_number":"68","_id":"19028","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)"},"date_updated":"2025-12-02T13:58:56Z","OA_type":"hybrid","author":[{"full_name":"Sakai, Hiroyuki","last_name":"Sakai","first_name":"Hiroyuki"},{"full_name":"Freude, Christian","first_name":"Christian","last_name":"Freude"},{"first_name":"Thomas","id":"4718F954-F248-11E8-B48F-1D18A9856A87","last_name":"Auzinger","orcid":"0000-0002-1546-3265","full_name":"Auzinger, Thomas"},{"full_name":"Hahn, David","first_name":"David","id":"357A6A66-F248-11E8-B48F-1D18A9856A87","last_name":"Hahn"},{"first_name":"Michael","last_name":"Wimmer","full_name":"Wimmer, Michael"}],"publication_status":"published","date_published":"2024-12-03T00:00:00Z","file":[{"file_id":"19563","access_level":"open_access","file_name":"2024_SIGGRAPH_Sakai.pdf","creator":"dernst","success":1,"date_created":"2025-04-15T12:53:24Z","relation":"main_file","checksum":"89f63b9237224362ec33430af9152700","date_updated":"2025-04-15T12:53:24Z","file_size":14791980,"content_type":"application/pdf"}],"file_date_updated":"2025-04-15T12:53:24Z","isi":1,"title":"A statistical approach to Monte Carlo denoising","doi":"10.1145/3680528.3687591"},{"has_accepted_license":"1","ddc":["000"],"publisher":"Transactions on Machine Learning Research","publication_identifier":{"eissn":["2835-8856"]},"scopus_import":"1","abstract":[{"lang":"eng","text":"Continual learning is a subfield of machine learning, which aims to allow machine learning models to continuously learn on new data, by accumulating knowledge without forgetting what was learned in the past. In this work, we take a step back, and ask: \"Why should one care about continual learning in the first place?\". We set the stage by examining recent continual learning papers published at four major machine learning conferences, and show that memory-constrained settings dominate the field. Then, we discuss five open problems in machine learning, and even though they might seem unrelated to continual learning at first sight, we show that continual learning will inevitably be part of their solution. These problems are model editing, personalization and specialization, on-device learning, faster (re-)training and reinforcement learning. Finally, by comparing the desiderata from these unsolved problems and the current assumptions in continual learning, we highlight and discuss four future directions for continual learning research. We hope that this work offers an interesting perspective on the future of continual learning, while displaying its potential value and the paths we have to pursue in order to make it successful. This work is the result of the many discussions the authors had at the Dagstuhl seminar on Deep Continual Learning, in March 2023."}],"day":"12","volume":2024,"month":"04","oa":1,"arxiv":1,"article_processing_charge":"No","OA_place":"publisher","external_id":{"arxiv":["2311.11908"]},"publication":"Transactions on Machine Learning Research","article_type":"original","type":"journal_article","year":"2024","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","alternative_title":["TMLR"],"intvolume":" 2024","date_created":"2025-03-16T23:01:25Z","quality_controlled":"1","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)"},"date_updated":"2025-03-20T09:21:02Z","_id":"19408","oa_version":"Published Version","language":[{"iso":"eng"}],"department":[{"_id":"ChLa"}],"citation":{"ieee":"E. Verwimp et al., “Continual learning: Applications and the road forward,” Transactions on Machine Learning Research, vol. 2024. Transactions on Machine Learning Research, 2024.","mla":"Verwimp, Eli, et al. “Continual Learning: Applications and the Road Forward.” Transactions on Machine Learning Research, vol. 2024, Transactions on Machine Learning Research, 2024.","ista":"Verwimp E, Aljundi R, Ben-David S, Bethge M, Cossu A, Gepperth A, Hayes TL, Hüllermeier E, Kanan C, Kudithipudi D, Lampert C, Mundt M, Pascanu R, Popescu A, Tolias AS, Van De Weijer J, Liu B, Lomonaco V, Tuytelaars T, Van De Ven GM. 2024. Continual learning: Applications and the road forward. Transactions on Machine Learning Research. 2024.","ama":"Verwimp E, Aljundi R, Ben-David S, et al. Continual learning: Applications and the road forward. Transactions on Machine Learning Research. 2024;2024.","short":"E. Verwimp, R. Aljundi, S. Ben-David, M. Bethge, A. Cossu, A. Gepperth, T.L. Hayes, E. Hüllermeier, C. Kanan, D. Kudithipudi, C. Lampert, M. Mundt, R. Pascanu, A. Popescu, A.S. Tolias, J. Van De Weijer, B. Liu, V. Lomonaco, T. Tuytelaars, G.M. Van De Ven, Transactions on Machine Learning Research 2024 (2024).","apa":"Verwimp, E., Aljundi, R., Ben-David, S., Bethge, M., Cossu, A., Gepperth, A., … Van De Ven, G. M. (2024). Continual learning: Applications and the road forward. Transactions on Machine Learning Research. Transactions on Machine Learning Research.","chicago":"Verwimp, Eli, Rahaf Aljundi, Shai Ben-David, Matthias Bethge, Andrea Cossu, Alexander Gepperth, Tyler L. Hayes, et al. “Continual Learning: Applications and the Road Forward.” Transactions on Machine Learning Research. Transactions on Machine Learning Research, 2024."},"status":"public","date_published":"2024-04-12T00:00:00Z","author":[{"last_name":"Verwimp","first_name":"Eli","full_name":"Verwimp, Eli"},{"full_name":"Aljundi, Rahaf","last_name":"Aljundi","first_name":"Rahaf"},{"last_name":"Ben-David","first_name":"Shai","full_name":"Ben-David, Shai"},{"first_name":"Matthias","last_name":"Bethge","full_name":"Bethge, Matthias"},{"full_name":"Cossu, Andrea","first_name":"Andrea","last_name":"Cossu"},{"last_name":"Gepperth","first_name":"Alexander","full_name":"Gepperth, Alexander"},{"full_name":"Hayes, Tyler L.","first_name":"Tyler L.","last_name":"Hayes"},{"full_name":"Hüllermeier, Eyke","last_name":"Hüllermeier","first_name":"Eyke"},{"last_name":"Kanan","first_name":"Christopher","full_name":"Kanan, Christopher"},{"first_name":"Dhireesha","last_name":"Kudithipudi","full_name":"Kudithipudi, Dhireesha"},{"orcid":"0000-0001-8622-7887","last_name":"Lampert","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","first_name":"Christoph","full_name":"Lampert, Christoph"},{"last_name":"Mundt","first_name":"Martin","full_name":"Mundt, Martin"},{"last_name":"Pascanu","first_name":"Razvan","full_name":"Pascanu, Razvan"},{"full_name":"Popescu, Adrian","first_name":"Adrian","last_name":"Popescu"},{"last_name":"Tolias","first_name":"Andreas S.","full_name":"Tolias, Andreas S."},{"full_name":"Van De Weijer, Joost","first_name":"Joost","last_name":"Van De Weijer"},{"last_name":"Liu","first_name":"Bing","full_name":"Liu, Bing"},{"full_name":"Lomonaco, Vincenzo","first_name":"Vincenzo","last_name":"Lomonaco"},{"full_name":"Tuytelaars, Tinne","first_name":"Tinne","last_name":"Tuytelaars"},{"first_name":"Gido M.","last_name":"Van De Ven","full_name":"Van De Ven, Gido 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Polykarpos","last_name":"Athanasiadis","full_name":"Athanasiadis, Anastasios Polykarpos"},{"full_name":"Pearmund, Charlie","first_name":"Charlie","last_name":"Pearmund"},{"last_name":"Spanlang","first_name":"Bernhard","full_name":"Spanlang, Bernhard"},{"full_name":"Alvarez, Elena","last_name":"Alvarez","first_name":"Elena"},{"full_name":"Sanchez, Mavi","last_name":"Sanchez","first_name":"Mavi"},{"full_name":"Giner, Arantxa","last_name":"Giner","first_name":"Arantxa"},{"last_name":"Jia","first_name":"Tianye","full_name":"Jia, Tianye"},{"full_name":"Gong, Yanting","last_name":"Gong","first_name":"Yanting"},{"full_name":"Xia, Yunman","first_name":"Yunman","last_name":"Xia"},{"last_name":"Chang","first_name":"Xiao","full_name":"Chang, Xiao"},{"full_name":"Calhoun, Vince","last_name":"Calhoun","first_name":"Vince"},{"full_name":"Liu, Jingyu","first_name":"Jingyu","last_name":"Liu"},{"full_name":"Schwalber, Ameli","last_name":"Schwalber","first_name":"Ameli"},{"first_name":"Paul","last_name":"Thompson","full_name":"Thompson, Paul"},{"first_name":"Nicholas","last_name":"Clinton","full_name":"Clinton, Nicholas"},{"first_name":"Sylvane","last_name":"Desrivières","full_name":"Desrivières, Sylvane"},{"first_name":"Allan H.","last_name":"Young","full_name":"Young, Allan H."},{"full_name":"Stahl, Bernd","first_name":"Bernd","last_name":"Stahl"},{"last_name":"Ogoh","first_name":"George","full_name":"Ogoh, George"}],"date_published":"2024-10-01T00:00:00Z","doi":"10.1038/s44220-024-00316-z","title":"Large-scale population data enrichment in mental health research","OA_type":"closed access","_id":"19446","date_updated":"2025-03-25T08:28:39Z","quality_controlled":"1","date_created":"2025-03-23T23:01:28Z","intvolume":" 2","language":[{"iso":"eng"}],"oa_version":"None","status":"public","citation":{"ista":"Nees F, Renner P, Holz NE, Polemiti E, Siehl S, Hese S, Schepanski K, Schumann G, Walter H, Heinz A, Ralser M, Twardziok S, Vaidya N, Bernas A, Serin E, Jentsch M, Hitchen E, Kebir H, Lett TA, Roy JC, Eils R, Taron UH, Schütz T, Banks J, Banaschewski T, Jansone K, Christmann N, Meyer-Lindenberg A, Tost H, Holz N, Schwarz E, Stringaris A, Neidhart M, Seefried B, Aden R, Andreassen OA, Westlye LT, Van Der Meer D, Fernandez S, Kjelkenes R, Ask H, Rapp M, Tschorn M, Böttger SJ, Marquand A, Novarino G, Marr L, Slater M, Viapiana GF, Orosa FE, Gallego J, Pastor A, Forstner AJ, Hoffmann P, Nöthen MM, Claus I, Miller A, Mathey CM, Heilmann-Heimbach S, Sommer P, Patraskaki M, Wilbertz J, Schmitt K, Jirsa V, Petkoski S, Pitel S, Otten L, Athanasiadis AP, Pearmund C, Spanlang B, Alvarez E, Sanchez M, Giner A, Jia T, Gong Y, Xia Y, Chang X, Calhoun V, Liu J, Schwalber A, Thompson P, Clinton N, Desrivières S, Young AH, Stahl B, Ogoh G. 2024. Large-scale population data enrichment in mental health research. Nature Mental Health. 2(10), 1124–1127.","ama":"Nees F, Renner P, Holz NE, et al. Large-scale population data enrichment in mental health research. Nature Mental Health. 2024;2(10):1124-1127. doi:10.1038/s44220-024-00316-z","mla":"Nees, Frauke, et al. “Large-Scale Population Data Enrichment in Mental Health Research.” Nature Mental Health, vol. 2, no. 10, Springer Nature, 2024, pp. 1124–27, doi:10.1038/s44220-024-00316-z.","ieee":"F. Nees et al., “Large-scale population data enrichment in mental health research,” Nature Mental Health, vol. 2, no. 10. Springer Nature, pp. 1124–1127, 2024.","apa":"Nees, F., Renner, P., Holz, N. E., Polemiti, E., Siehl, S., Hese, S., … Ogoh, G. (2024). Large-scale population data enrichment in mental health research. Nature Mental Health. Springer Nature. https://doi.org/10.1038/s44220-024-00316-z","chicago":"Nees, Frauke, Paul Renner, Nathalie E. Holz, Elli Polemiti, Sebastian Siehl, Sören Hese, Kerstin Schepanski, et al. “Large-Scale Population Data Enrichment in Mental Health Research.” Nature Mental Health. Springer Nature, 2024. https://doi.org/10.1038/s44220-024-00316-z.","short":"F. Nees, P. Renner, N.E. Holz, E. Polemiti, S. Siehl, S. Hese, K. Schepanski, G. Schumann, H. Walter, A. Heinz, M. Ralser, S. Twardziok, N. Vaidya, A. Bernas, E. Serin, M. Jentsch, E. Hitchen, H. Kebir, T.A. Lett, J.C. Roy, R. Eils, U.H. Taron, T. Schütz, J. Banks, T. Banaschewski, K. Jansone, N. Christmann, A. Meyer-Lindenberg, H. Tost, N. Holz, E. Schwarz, A. Stringaris, M. Neidhart, B. Seefried, R. Aden, O.A. Andreassen, L.T. Westlye, D. Van Der Meer, S. Fernandez, R. Kjelkenes, H. Ask, M. Rapp, M. Tschorn, S.J. Böttger, A. Marquand, G. Novarino, L. Marr, M. Slater, G.F. Viapiana, F.E. Orosa, J. Gallego, A. Pastor, A.J. Forstner, P. Hoffmann, M.M. Nöthen, I. Claus, A. Miller, C.M. Mathey, S. Heilmann-Heimbach, P. Sommer, M. Patraskaki, J. Wilbertz, K. Schmitt, V. Jirsa, S. Petkoski, S. Pitel, L. Otten, A.P. Athanasiadis, C. Pearmund, B. Spanlang, E. Alvarez, M. Sanchez, A. Giner, T. Jia, Y. Gong, Y. Xia, X. Chang, V. Calhoun, J. Liu, A. Schwalber, P. Thompson, N. Clinton, S. Desrivières, A.H. Young, B. Stahl, G. Ogoh, Nature Mental Health 2 (2024) 1124–1127."},"department":[{"_id":"GaNo"}],"article_type":"letter_note","type":"journal_article","year":"2024","fulldoi":"https://doi.org/10.1038/s44220-024-00316-z","issue":"10","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"Springer Nature","acknowledgement":"Funded by the European Union. Complementary funding was received by the 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 and UKRI cannot be held responsible for them. This work received also support from 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 (CoviDrug)) and the National Natural Science Foundation of China grant 82150710554.","volume":2,"day":"01","abstract":[{"text":"This Comment explores new approaches to enrich large-scale population data, including incorporating macro-environmental and digital health measures.","lang":"eng"}],"scopus_import":"1","publication_identifier":{"eissn":["2731-6076"]},"month":"10","publication":"Nature Mental Health","article_processing_charge":"No"},{"citation":{"chicago":"Douglass, Amelia M., Hakan Kucukdereli, Joseph C. Madara, Daqing Wang, Chen Wu, Elijah D. Lowenstein, Jenkang Tao, and Bradford B. Lowell. “Acute and Circadian Feedforward Regulation of Agouti-Related Peptide Hunger Neurons.” Cell Metabolism. Elsevier, 2024. https://doi.org/10.1016/j.cmet.2024.11.009.","apa":"Douglass, A. M., Kucukdereli, H., Madara, J. C., Wang, D., Wu, C., Lowenstein, E. D., … Lowell, B. B. (2024). Acute and circadian feedforward regulation of agouti-related peptide hunger neurons. Cell Metabolism. Elsevier. https://doi.org/10.1016/j.cmet.2024.11.009","short":"A.M. Douglass, H. Kucukdereli, J.C. Madara, D. Wang, C. Wu, E.D. Lowenstein, J. Tao, B.B. Lowell, Cell Metabolism 37 (2024) 708–722.e5.","ista":"Douglass AM, Kucukdereli H, Madara JC, Wang D, Wu C, Lowenstein ED, Tao J, Lowell BB. 2024. Acute and circadian feedforward regulation of agouti-related peptide hunger neurons. Cell Metabolism. 37(3), 708–722.e5.","ama":"Douglass AM, Kucukdereli H, Madara JC, et al. Acute and circadian feedforward regulation of agouti-related peptide hunger neurons. Cell Metabolism. 2024;37(3):708-722.e5. doi:10.1016/j.cmet.2024.11.009","mla":"Douglass, Amelia M., et al. “Acute and Circadian Feedforward Regulation of Agouti-Related Peptide Hunger Neurons.” Cell Metabolism, vol. 37, no. 3, Elsevier, 2024, p. 708–722.e5, doi:10.1016/j.cmet.2024.11.009.","ieee":"A. M. Douglass et al., “Acute and circadian feedforward regulation of agouti-related peptide hunger neurons,” Cell Metabolism, vol. 37, no. 3. Elsevier, p. 708–722.e5, 2024."},"status":"public","oa_version":"None","language":[{"iso":"eng"}],"extern":"1","date_created":"2025-04-03T12:27:39Z","intvolume":" 37","_id":"19470","date_updated":"2025-07-10T11:51:40Z","quality_controlled":"1","OA_type":"closed access","doi":"10.1016/j.cmet.2024.11.009","title":"Acute and circadian feedforward regulation of agouti-related peptide hunger neurons","page":"708-722.e5","author":[{"first_name":"Amelia May Barnett","last_name":"Douglass","orcid":"0000-0001-5398-6473","id":"de5f6fda-80fb-11ef-996f-a8c4ecd8e289","full_name":"Douglass, Amelia May Barnett"},{"full_name":"Kucukdereli, Hakan","first_name":"Hakan","last_name":"Kucukdereli"},{"full_name":"Madara, Joseph C.","first_name":"Joseph C.","last_name":"Madara"},{"full_name":"Wang, Daqing","first_name":"Daqing","last_name":"Wang"},{"full_name":"Wu, Chen","first_name":"Chen","last_name":"Wu"},{"full_name":"Lowenstein, Elijah D.","first_name":"Elijah D.","last_name":"Lowenstein"},{"last_name":"Tao","first_name":"Jenkang","full_name":"Tao, Jenkang"},{"full_name":"Lowell, Bradford B.","last_name":"Lowell","first_name":"Bradford B."}],"date_published":"2024-03-04T00:00:00Z","publication_status":"published","pmid":1,"article_processing_charge":"No","external_id":{"pmid":["39719709"]},"publication":"Cell Metabolism","month":"03","abstract":[{"text":"When food is freely available, eating occurs without energy deficit. While agouti-related peptide (AgRP) neurons are likely involved, their activation is thought to require negative energy balance. To investigate this, we implemented long-term, continuous in vivo fiber-photometry recordings in mice. We discovered new forms of AgRP neuron regulation, including fast pre-ingestive decreases in activity and unexpectedly rapid activation by fasting. Furthermore, AgRP neuron activity has a circadian rhythm that peaks concurrent with the daily feeding onset. Importantly, this rhythm persists when nutrition is provided via constant-rate gastric infusions. Hence, it is not secondary to a circadian feeding rhythm. The AgRP neuron rhythm is driven by the circadian clock, the suprachiasmatic nucleus (SCN), as SCN ablation abolishes the circadian rhythm in AgRP neuron activity and feeding. The SCN activates AgRP neurons via excitatory afferents from thyrotrophin-releasing hormone-expressing neurons in the dorsomedial hypothalamus (DMHTrh neurons) to drive daily feeding rhythms.","lang":"eng"}],"scopus_import":"1","publication_identifier":{"issn":["1550-4131"]},"volume":37,"day":"04","publisher":"Elsevier","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","issue":"3","year":"2024","fulldoi":"https://doi.org/10.1016/j.cmet.2024.11.009","type":"journal_article","article_type":"original"},{"volume":2024,"day":"01","abstract":[{"text":"Consider the family of elliptic curves En:y2=x3+n2, where n varies over positive cubefree integers. There is a rational 3-isogeny ϕ from En to E^n:y2=x3−27n2 and a dual isogeny ϕ^:E^n→En. We show that for almost all n, the rank of Selϕ(En) is 0, and the rank of Selϕ^(E^n) is determined by the number of prime factors of n that are congruent to 2mod3 and the congruence class of nmod9.","lang":"eng"}],"scopus_import":"1","publication_identifier":{"eissn":["1687-0247"],"issn":["1073-7928"]},"publisher":"Oxford University Press","acknowledgement":"The author would like to thank Peter Koymans and Carlo Pagano for helpful discussions.","publication":"International Mathematics Research Notices","OA_place":"repository","external_id":{"arxiv":["2211.06062"]},"article_processing_charge":"No","arxiv":1,"oa":1,"month":"05","type":"journal_article","article_type":"original","issue":"9","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2024","fulldoi":"https://doi.org/10.1093/imrn/rnad266","_id":"19486","date_updated":"2025-07-10T11:51:44Z","quality_controlled":"1","date_created":"2025-04-05T10:50:33Z","intvolume":" 2024","status":"public","citation":{"short":"S. Chan, International Mathematics Research Notices 2024 (2024) 7571–7593.","chicago":"Chan, Stephanie. “The 3-Isogeny Selmer Groups of the Elliptic Curves Y2=x3+n2.” International Mathematics Research Notices. Oxford University Press, 2024. https://doi.org/10.1093/imrn/rnad266.","apa":"Chan, S. (2024). The 3-isogeny selmer groups of the elliptic curves y2=x3+n2. International Mathematics Research Notices. Oxford University Press. https://doi.org/10.1093/imrn/rnad266","ieee":"S. Chan, “The 3-isogeny selmer groups of the elliptic curves y2=x3+n2,” International Mathematics Research Notices, vol. 2024, no. 9. Oxford University Press, pp. 7571–7593, 2024.","ista":"Chan S. 2024. The 3-isogeny selmer groups of the elliptic curves y2=x3+n2. International Mathematics Research Notices. 2024(9), 7571–7593.","ama":"Chan S. The 3-isogeny selmer groups of the elliptic curves y2=x3+n2. International Mathematics Research Notices. 2024;2024(9):7571-7593. doi:10.1093/imrn/rnad266","mla":"Chan, Stephanie. “The 3-Isogeny Selmer Groups of the Elliptic Curves Y2=x3+n2.” International Mathematics Research Notices, vol. 2024, no. 9, Oxford University Press, 2024, pp. 7571–93, doi:10.1093/imrn/rnad266."},"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2211.06062"}],"language":[{"iso":"eng"}],"extern":"1","oa_version":"Preprint","doi":"10.1093/imrn/rnad266","title":"The 3-isogeny selmer groups of the elliptic curves y2=x3+n2","page":"7571-7593","publication_status":"published","date_published":"2024-05-01T00:00:00Z","author":[{"full_name":"Chan, Yik Tung","last_name":"Chan","orcid":"0000-0001-8467-4106","id":"c4c0afc8-9262-11ed-9231-d8b0bc743af1","first_name":"Yik Tung"}],"OA_type":"green"},{"author":[{"full_name":"Crisostomi, Donato","first_name":"Donato","last_name":"Crisostomi"},{"full_name":"Fumero, Marco","first_name":"Marco","id":"1c1593eb-393f-11ef-bb8e-ab4f1e979650","last_name":"Fumero"},{"full_name":"Baieri, Daniele","first_name":"Daniele","last_name":"Baieri"},{"full_name":"Bernard, Florian","first_name":"Florian","last_name":"Bernard"},{"full_name":"Rodolà, Emanuele","last_name":"Rodolà","first_name":"Emanuele"}],"publication_status":"published","date_published":"2024-12-20T00:00:00Z","title":"C2M3: Cycle-consistent multi-model merging","OA_type":"green","alternative_title":["Advances in Neural Information Processing Systems"],"date_created":"2025-04-06T22:01:32Z","intvolume":" 37","date_updated":"2025-05-14T11:36:59Z","_id":"19517","quality_controlled":"1","oa_version":"Preprint","ec_funded":1,"language":[{"iso":"eng"}],"citation":{"apa":"Crisostomi, D., Fumero, M., Baieri, D., Bernard, F., & Rodolà, E. (2024). C2M3: Cycle-consistent multi-model merging. In 38th Conference on Neural Information Processing Systems (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.","chicago":"Crisostomi, Donato, Marco Fumero, Daniele Baieri, Florian Bernard, and Emanuele Rodolà. “C2M3: Cycle-Consistent Multi-Model Merging.” In 38th Conference on Neural Information Processing Systems, 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.","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.","ama":"Crisostomi D, Fumero M, Baieri D, Bernard F, Rodolà E. C2M3: Cycle-consistent multi-model merging. In: 38th Conference on Neural Information Processing Systems. Vol 37. Neural Information Processing Systems Foundation; 2024.","mla":"Crisostomi, Donato, et al. “C2M3: Cycle-Consistent Multi-Model Merging.” 38th Conference on Neural Information Processing Systems, vol. 37, 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 38th Conference on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37."},"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2405.17897"}],"department":[{"_id":"FrLo"}],"status":"public","type":"conference","year":"2024","conference":{"start_date":"2024-12-09","name":"NeurIPS: Neural Information Processing Systems","location":"Vancouver, Canada","end_date":"2024-12-15"},"project":[{"grant_number":"101034413","name":"IST-BRIDGE: International postdoctoral program","_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c","call_identifier":"H2020"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","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.","corr_author":"1","publisher":"Neural Information Processing Systems Foundation","scopus_import":"1","abstract":[{"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.","lang":"eng"}],"publication_identifier":{"issn":["1049-5258"]},"volume":37,"day":"20","month":"12","article_processing_charge":"No","arxiv":1,"oa":1,"OA_place":"repository","external_id":{"arxiv":["2405.17897"]},"publication":"38th Conference on Neural Information Processing Systems"},{"external_id":{"arxiv":["2408.17163"]},"OA_place":"repository","publication":"38th Conference on Neural Information Processing Systems","oa":1,"arxiv":1,"article_processing_charge":"No","month":"12","day":"20","volume":37,"publication_identifier":{"issn":["1049-5258"]},"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."}],"scopus_import":"1","publisher":"Neural Information Processing Systems Foundation","corr_author":"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.","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","conference":{"start_date":"2024-12-09","end_date":"2024-12-15","name":"NeurIPS: Neural Information Processing Systems","location":"Vancouver, Canada"},"project":[{"name":"IST-BRIDGE: International postdoctoral program","call_identifier":"H2020","_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c","grant_number":"101034413"}],"year":"2024","type":"conference","acknowledged_ssus":[{"_id":"CampIT"}],"status":"public","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2408.17163","open_access":"1"}],"department":[{"_id":"DaAl"},{"_id":"MaMo"}],"citation":{"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 38th Conference on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.","mla":"Wu, Diyuan, et al. “The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information.” 38th Conference on Neural Information Processing Systems, vol. 37, Neural Information Processing Systems Foundation, 2024.","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: 38th Conference on Neural Information Processing Systems. Vol 37. Neural Information Processing Systems Foundation; 2024.","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. 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Vancouver, Canada: Neural Information Processing Systems Foundation."},"language":[{"iso":"eng"}],"ec_funded":1,"oa_version":"Preprint","quality_controlled":"1","_id":"19518","date_updated":"2025-05-14T11:37:10Z","intvolume":" 37","date_created":"2025-04-06T22:01:32Z","alternative_title":["Advances in Neural Information Processing Systems"],"OA_type":"green","title":"The iterative optimal brain surgeon: Faster sparse recovery by leveraging second-order information","date_published":"2024-12-20T00:00:00Z","author":[{"id":"1a5914c2-896a-11ed-bdf8-fb80621a0635","last_name":"Wu","first_name":"Diyuan","full_name":"Wu, Diyuan"},{"last_name":"Modoranu","id":"449f7a18-f128-11eb-9611-9b430c0c6333","first_name":"Ionut-Vlad","full_name":"Modoranu, Ionut-Vlad"},{"full_name":"Safaryan, Mher","last_name":"Safaryan","id":"dd546b39-0804-11ed-9c55-ef075c39778d","first_name":"Mher"},{"full_name":"Kuznedelev, Denis","first_name":"Denis","last_name":"Kuznedelev"},{"full_name":"Alistarh, Dan-Adrian","first_name":"Dan-Adrian","orcid":"0000-0003-3650-940X","last_name":"Alistarh","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87"}],"publication_status":"published"},{"file":[{"file_id":"19521","access_level":"open_access","file_name":"2024_NeurIPS_Malinovskii.pdf","date_created":"2025-04-07T09:17:10Z","success":1,"creator":"dernst","date_updated":"2025-04-07T09:17:10Z","checksum":"54d36f947887e26d0e568b512167001a","relation":"main_file","file_size":939712,"content_type":"application/pdf"}],"publication_status":"published","author":[{"full_name":"Malinovskii, Vladimir","last_name":"Malinovskii","first_name":"Vladimir"},{"full_name":"Mazur, Denis","last_name":"Mazur","first_name":"Denis"},{"last_name":"Ilin","first_name":"Ivan","full_name":"Ilin, Ivan"},{"full_name":"Kuznedelev, Denis","first_name":"Denis","last_name":"Kuznedelev"},{"full_name":"Burlachenko, Konstantin","first_name":"Konstantin","last_name":"Burlachenko"},{"full_name":"Yi, Kai","last_name":"Yi","first_name":"Kai"},{"id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-3650-940X","last_name":"Alistarh","first_name":"Dan-Adrian","full_name":"Alistarh, Dan-Adrian"},{"first_name":"Peter","last_name":"Richtarik","full_name":"Richtarik, Peter"}],"date_published":"2024-12-20T00:00:00Z","file_date_updated":"2025-04-07T09:17:10Z","title":"PV-tuning: Beyond straight-through estimation for extreme LLM compression","OA_type":"gold","alternative_title":["Advances in Neural Information Processing Systems"],"quality_controlled":"1","date_updated":"2025-05-14T10:49:20Z","_id":"19519","intvolume":" 37","date_created":"2025-04-06T22:01:32Z","language":[{"iso":"eng"}],"oa_version":"Published Version","status":"public","department":[{"_id":"DaAl"}],"citation":{"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.","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 38th Conference on Neural Information Processing Systems, 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 38th Conference on Neural Information Processing Systems (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.","ieee":"V. Malinovskii et al., “PV-tuning: Beyond straight-through estimation for extreme LLM compression,” in 38th Conference on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.","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.","ama":"Malinovskii V, Mazur D, Ilin I, et al. PV-tuning: Beyond straight-through estimation for extreme LLM compression. In: 38th Conference on Neural Information Processing Systems. Vol 37. Neural Information Processing Systems Foundation; 2024.","mla":"Malinovskii, Vladimir, et al. “PV-Tuning: Beyond Straight-through Estimation for Extreme LLM Compression.” 38th Conference on Neural Information Processing Systems, vol. 37, Neural Information Processing Systems Foundation, 2024."},"type":"conference","conference":{"name":"NeurIPS: Neural Information Processing Systems","location":"Vancouver, Canada","end_date":"2024-12-15","start_date":"2024-12-10"},"year":"2024","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"Neural Information Processing Systems Foundation","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.","has_accepted_license":"1","ddc":["000"],"day":"20","volume":37,"publication_identifier":{"issn":["1049-5258"],"isbn":["9798331314385"]},"scopus_import":"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"}],"month":"12","publication":"38th Conference on Neural Information Processing Systems","OA_place":"publisher","external_id":{"arxiv":["2405.14852"]},"oa":1,"arxiv":1,"article_processing_charge":"No"},{"oa_version":"Preprint","language":[{"iso":"eng"}],"month":"09","department":[{"_id":"LoSw"},{"_id":"TiVo"},{"_id":"Bio"},{"_id":"NiBa"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.1101/2024.09.20.614050"}],"oa":1,"citation":{"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.).","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.” BioRxiv, n.d. https://doi.org/10.1101/2024.09.20.614050.","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. bioRxiv. https://doi.org/10.1101/2024.09.20.614050","ieee":"D. Vijatovic et al., “Spinal neuron diversity scales exponentially with swim-to-limb transformation during frog metamorphosis,” bioRxiv. .","ama":"Vijatovic D, Toma FA, Harrington ZP, et al. Spinal neuron diversity scales exponentially with swim-to-limb transformation during frog metamorphosis. bioRxiv. doi:10.1101/2024.09.20.614050","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, 10.1101/2024.09.20.614050.","mla":"Vijatovic, David, et al. “Spinal Neuron Diversity Scales Exponentially with Swim-to-Limb Transformation during Frog Metamorphosis.” BioRxiv, doi:10.1101/2024.09.20.614050."},"article_processing_charge":"No","OA_place":"repository","publication":"bioRxiv","status":"public","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.). ","corr_author":"1","abstract":[{"lang":"eng","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."}],"date_created":"2025-04-07T08:48:28Z","day":"27","date_updated":"2025-05-14T11:40:13Z","_id":"19520","fulldoi":"https://doi.org/10.1101/2024.09.20.614050","project":[{"grant_number":"FTI21-D-046","_id":"bd73af52-d553-11ed-ba76-912049f0ac7a","name":"Development of V1 interneuron diversity during swim-to-walk transition of Xenopus metamorphosis"},{"grant_number":"101041551","name":"Development and Evolution of Tetrapod Motor Circuits","_id":"ebb66355-77a9-11ec-83b8-b8ac210a4dae"},{"_id":"c08e9ad1-5a5b-11eb-8a69-9d1cf3b07473","name":"Tools for automation and feedback microscopy","grant_number":"CZI01"}],"OA_type":"green","year":"2024","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"full_name":"Vijatovic, David","last_name":"Vijatovic","id":"cf391e77-ec3c-11ea-a124-d69323410b58","first_name":"David"},{"full_name":"Toma, Florina Alexandra ","id":"2f73f876-f128-11eb-9611-b96b5a30cb0e","last_name":"Toma","first_name":"Florina Alexandra "},{"full_name":"Harrington, Zoe P","orcid":"0009-0008-0158-4032","last_name":"Harrington","id":"a8144562-32c9-11ee-b5ce-d9800628bda2","first_name":"Zoe P"},{"last_name":"Sommer","orcid":"0000-0003-1216-9105","id":"4DF26D8C-F248-11E8-B48F-1D18A9856A87","first_name":"Christoph M","full_name":"Sommer, Christoph M"},{"id":"4E01D6B4-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-9843-3522","last_name":"Hauschild","first_name":"Robert","full_name":"Hauschild, Robert"},{"full_name":"Trevisan, Alexandra J.","first_name":"Alexandra J.","last_name":"Trevisan"},{"full_name":"Chapman, Phillip","first_name":"Phillip","last_name":"Chapman"},{"full_name":"Julseth, Mara","last_name":"Julseth","id":"1cf464b2-dc7d-11ea-9b2f-f9b1aa9417d1","first_name":"Mara"},{"full_name":"Brenner-Morton, Susan","first_name":"Susan","last_name":"Brenner-Morton"},{"last_name":"Gabitto","first_name":"Mariano I.","full_name":"Gabitto, Mariano I."},{"last_name":"Dasen","first_name":"Jeremy S.","full_name":"Dasen, Jeremy S."},{"full_name":"Bikoff, Jay B.","last_name":"Bikoff","first_name":"Jay B."},{"id":"56BE8254-C4F0-11E9-8E45-0B23E6697425","last_name":"Sweeney","orcid":"0000-0001-9242-5601","first_name":"Lora Beatrice Jaeger","full_name":"Sweeney, Lora Beatrice Jaeger"}],"acknowledged_ssus":[{"_id":"Bio"}],"publication_status":"submitted","date_published":"2024-09-27T00:00:00Z","title":"Spinal neuron diversity scales exponentially with swim-to-limb transformation during frog metamorphosis","doi":"10.1101/2024.09.20.614050","type":"preprint"},{"publisher":"Zenodo","ddc":["000"],"has_accepted_license":"1","date_updated":"2025-09-30T12:46:33Z","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)"},"_id":"19800","day":"28","date_created":"2025-06-10T07:10:01Z","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"}],"month":"09","related_material":{"record":[{"status":"public","relation":"used_in_publication","id":"19796"}]},"oa_version":"Published Version","status":"public","OA_place":"repository","article_processing_charge":"No","citation":{"apa":"trinh, V. G., Park, K. H., Pastva, S., & Rozum, J. (2024). Mapping the attractor landscape of Boolean networks. Zenodo. https://doi.org/10.5281/ZENODO.13854759","chicago":"trinh, Van Giang, Kyu Hyong Park, Samuel Pastva, and Jordan Rozum. “Mapping the Attractor Landscape of Boolean Networks.” Zenodo, 2024. https://doi.org/10.5281/ZENODO.13854759.","short":"V.G. trinh, K.H. Park, S. Pastva, J. Rozum, (2024).","ama":"trinh VG, Park KH, Pastva S, Rozum J. Mapping the attractor landscape of Boolean networks. 2024. doi:10.5281/ZENODO.13854759","ista":"trinh VG, Park KH, Pastva S, Rozum J. 2024. Mapping the attractor landscape of Boolean networks, Zenodo, 10.5281/ZENODO.13854759.","mla":"trinh, Van Giang, et al. Mapping the Attractor Landscape of Boolean Networks. Zenodo, 2024, doi:10.5281/ZENODO.13854759.","ieee":"V. G. trinh, K. H. Park, S. Pastva, and J. Rozum, “Mapping the attractor landscape of Boolean networks.” Zenodo, 2024."},"oa":1,"department":[{"_id":"ToHe"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.5281/zenodo.13854760"}],"author":[{"full_name":"trinh, Van Giang","first_name":"Van Giang","last_name":"trinh"},{"first_name":"Kyu Hyong","last_name":"Park","full_name":"Park, Kyu Hyong"},{"orcid":"0000-0003-1993-0331","last_name":"Pastva","id":"07c5ea74-f61c-11ec-a664-aa7c5d957b2b","first_name":"Samuel","full_name":"Pastva, Samuel"},{"last_name":"Rozum","first_name":"Jordan","full_name":"Rozum, Jordan"}],"date_published":"2024-09-28T00:00:00Z","type":"research_data_reference","doi":"10.5281/ZENODO.13854759","title":"Mapping the attractor landscape of Boolean networks","year":"2024","fulldoi":"https://doi.org/10.5281/ZENODO.13854759","OA_type":"green","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87"},{"article_processing_charge":"No","oa":1,"OA_place":"publisher","publication":"Proceedings of the National Academy of Sciences","external_id":{"pmid":["39172781"]},"month":"08","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"}],"scopus_import":"1","publication_identifier":{"issn":["0027-8424"],"eissn":["1091-6490"]},"volume":121,"day":"27","has_accepted_license":"1","publisher":"National Academy of Sciences","issue":"35","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2024","fulldoi":"https://doi.org/10.1073/pnas.2318159121","type":"journal_article","article_type":"original","citation":{"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).","ama":"Sun F, Mishra S, Stockert U, et al. The Lorenz ratio as a guide to scattering contributions to transport in strongly correlated metals. Proceedings of the National Academy of Sciences. 2024;121(35). doi:10.1073/pnas.2318159121","mla":"Sun, Fei, et al. “The Lorenz Ratio as a Guide to Scattering Contributions to Transport in Strongly Correlated Metals.” Proceedings of the National Academy of Sciences, vol. 121, no. 35, National Academy of Sciences, 2024, doi:10.1073/pnas.2318159121.","ieee":"F. Sun et al., “The Lorenz ratio as a guide to scattering contributions to transport in strongly correlated metals,” Proceedings of the National Academy of Sciences, 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.” Proceedings of the National Academy of Sciences. National Academy of Sciences, 2024. https://doi.org/10.1073/pnas.2318159121.","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. Proceedings of the National Academy of Sciences. National Academy of Sciences. https://doi.org/10.1073/pnas.2318159121","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)."},"main_file_link":[{"url":"https://doi.org/10.1073/pnas.2318159121","open_access":"1"}],"status":"public","oa_version":"Published Version","language":[{"iso":"eng"}],"extern":"1","date_created":"2025-06-10T09:12:41Z","intvolume":" 121","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)"},"_id":"19809","date_updated":"2025-06-10T11:50:48Z","quality_controlled":"1","OA_type":"hybrid","doi":"10.1073/pnas.2318159121","title":"The Lorenz ratio as a guide to scattering contributions to transport in strongly correlated metals","publication_status":"published","pmid":1,"author":[{"first_name":"Fei","last_name":"Sun","full_name":"Sun, Fei"},{"last_name":"Mishra","first_name":"Simli","full_name":"Mishra, Simli"},{"full_name":"Stockert, Ulrike","last_name":"Stockert","first_name":"Ulrike"},{"last_name":"Daou","first_name":"Ramzy","full_name":"Daou, Ramzy"},{"last_name":"Kikugawa","first_name":"Naoki","full_name":"Kikugawa, Naoki"},{"last_name":"Perry","first_name":"Robin S.","full_name":"Perry, Robin S."},{"last_name":"Hassinger","first_name":"Elena","full_name":"Hassinger, Elena"},{"first_name":"Sean A.","last_name":"Hartnoll","full_name":"Hartnoll, Sean A."},{"full_name":"Mackenzie, Andrew P.","first_name":"Andrew P.","last_name":"Mackenzie"},{"first_name":"Veronika","id":"23cb1cf6-2c7a-11ef-91a4-f72fc19f20b3","last_name":"Sunko","orcid":"0000-0003-2724-3523","full_name":"Sunko, Veronika"}],"date_published":"2024-08-27T00:00:00Z"},{"month":"07","DOAJ_listed":"1","oa":1,"article_processing_charge":"No","OA_place":"publisher","publication":"Physical Review X","publisher":"American Physical Society","publication_identifier":{"eissn":["2160-3308"]},"scopus_import":"1","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."}],"day":"22","volume":14,"fulldoi":"https://doi.org/10.1103/physrevx.14.031013","year":"2024","issue":"3","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_type":"original","type":"journal_article","oa_version":"Published Version","extern":"1","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://doi.org/10.1103/physrevx.14.031013","open_access":"1"}],"citation":{"ama":"Donoway E, Trevisan TV, Liebman-Peláez A, et al. Multimodal approach reveals the symmetry-breaking pathway to the broken helix in EuIn2As2. Physical Review X. 2024;14(3). doi:10.1103/physrevx.14.031013","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.” Physical Review X, vol. 14, no. 3, 031013, American Physical Society, 2024, doi:10.1103/physrevx.14.031013.","ieee":"E. Donoway et al., “Multimodal approach reveals the symmetry-breaking pathway to the broken helix in EuIn2As2,” Physical Review X, vol. 14, no. 3. American Physical Society, 2024.","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. Physical Review X. American Physical Society. https://doi.org/10.1103/physrevx.14.031013","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.” Physical Review X. American Physical Society, 2024. https://doi.org/10.1103/physrevx.14.031013.","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)."},"status":"public","intvolume":" 14","date_created":"2025-06-10T09:17:30Z","quality_controlled":"1","article_number":"031013","_id":"19816","date_updated":"2025-06-10T13:14:20Z","OA_type":"gold","publication_status":"published","author":[{"full_name":"Donoway, E.","last_name":"Donoway","first_name":"E."},{"full_name":"Trevisan, T. V.","last_name":"Trevisan","first_name":"T. V."},{"first_name":"A.","last_name":"Liebman-Peláez","full_name":"Liebman-Peláez, 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.","first_name":"Y.","last_name":"Sun"},{"full_name":"Soh, J. R.","last_name":"Soh","first_name":"J. R."},{"last_name":"Prabhakaran","first_name":"D.","full_name":"Prabhakaran, D."},{"first_name":"A. T.","last_name":"Boothroyd","full_name":"Boothroyd, A. T."},{"last_name":"Fernandes","first_name":"R. M.","full_name":"Fernandes, R. M."},{"full_name":"Analytis, J. G.","last_name":"Analytis","first_name":"J. G."},{"full_name":"Moore, J. E.","first_name":"J. E.","last_name":"Moore"},{"last_name":"Orenstein","first_name":"J.","full_name":"Orenstein, J."},{"full_name":"Sunko, Veronika","id":"23cb1cf6-2c7a-11ef-91a4-f72fc19f20b3","last_name":"Sunko","orcid":"0000-0003-2724-3523","first_name":"Veronika"}],"date_published":"2024-07-22T00:00:00Z","title":"Multimodal approach reveals the symmetry-breaking pathway to the broken helix in EuIn2As2","doi":"10.1103/physrevx.14.031013"},{"date_created":"2025-06-24T06:09:18Z","abstract":[{"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).","lang":"eng"}],"date_updated":"2025-09-30T13:41:56Z","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)"},"_id":"19884","day":"24","ddc":["000"],"has_accepted_license":"1","corr_author":"1","publisher":"Zenodo","citation":{"ieee":"E. 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Zenodo. https://doi.org/10.5281/ZENODO.14213091","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. https://doi.org/10.5281/ZENODO.14213091."},"article_processing_charge":"No","main_file_link":[{"url":"https://doi.org/10.5281/ZENODO.14213091","open_access":"1"}],"department":[{"_id":"DaAl"}],"oa":1,"status":"public","OA_place":"repository","oa_version":"Published Version","month":"11","related_material":{"record":[{"relation":"used_for_analysis_in","status":"public","id":"19877"}]},"doi":"10.5281/ZENODO.14213091","title":"MARLIN: Mixed-precision auto-regressive parallel inference on Large Language Models","type":"research_data_reference","date_published":"2024-11-24T00:00:00Z","author":[{"first_name":"Elias","id":"09a8f98d-ec99-11ea-ae11-c063a7b7fe5f","last_name":"Frantar","full_name":"Frantar, Elias"},{"full_name":"Castro, Roberto","first_name":"Roberto","last_name":"Castro"},{"full_name":"Chen, Jiale","id":"4d0a9064-1ff6-11ee-9fa6-ec046c604785","orcid":"0000-0001-5337-5875","last_name":"Chen","first_name":"Jiale"},{"full_name":"Hoefler, Torsten","last_name":"Hoefler","first_name":"Torsten"},{"first_name":"Dan-Adrian","orcid":"0000-0003-3650-940X","last_name":"Alistarh","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","full_name":"Alistarh, Dan-Adrian"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2024","fulldoi":"https://doi.org/10.5281/ZENODO.14213091"},{"intvolume":" 2","date_created":"2025-07-20T22:02:04Z","quality_controlled":"1","date_updated":"2025-07-22T08:59:10Z","_id":"20039","oa_version":"None","language":[{"iso":"eng"}],"department":[{"_id":"GaNo"}],"citation":{"ieee":"M. Neidhart et al., “A protocol for data harmonization in large cohorts,” Nature Mental Health, vol. 2, no. 10. Springer Nature, pp. 1134–1137, 2024.","mla":"Neidhart, Maja, et al. “A Protocol for Data Harmonization in Large Cohorts.” Nature Mental Health, vol. 2, no. 10, Springer Nature, 2024, pp. 1134–37, doi:10.1038/s44220-024-00315-0.","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. 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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.","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.” Nature Mental Health. Springer Nature, 2024. https://doi.org/10.1038/s44220-024-00315-0.","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. Nature Mental Health. Springer Nature. https://doi.org/10.1038/s44220-024-00315-0"},"status":"public","date_published":"2024-10-01T00:00:00Z","author":[{"first_name":"Maja","last_name":"Neidhart","full_name":"Neidhart, Maja"},{"first_name":"Rikka","last_name":"Kjelkenes","full_name":"Kjelkenes, Rikka"},{"full_name":"Jansone, Karina","last_name":"Jansone","first_name":"Karina"},{"last_name":"Rehák Bučková","first_name":"Barbora","full_name":"Rehák Bučková, Barbora"},{"full_name":"Holz, Nathalie","first_name":"Nathalie","last_name":"Holz"},{"last_name":"Nees","first_name":"Frauke","full_name":"Nees, Frauke"},{"last_name":"Walter","first_name":"Henrik","full_name":"Walter, Henrik"},{"full_name":"Schumann, Gunter","first_name":"Gunter","last_name":"Schumann"},{"first_name":"Michael A.","last_name":"Rapp","full_name":"Rapp, Michael A."},{"full_name":"Banaschewski, Tobias","first_name":"Tobias","last_name":"Banaschewski"},{"first_name":"Emanuel","last_name":"Schwarz","full_name":"Schwarz, 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Meer","first_name":"Dennis","full_name":"Van Der Meer, Dennis"},{"last_name":"Westlye","first_name":"Lars T.","full_name":"Westlye, Lars T."},{"last_name":"Andreassen","first_name":"Ole A.","full_name":"Andreassen, Ole A."},{"first_name":"Rieke","last_name":"Aden","full_name":"Aden, Rieke"},{"full_name":"Seefried, Beke","last_name":"Seefried","first_name":"Beke"},{"full_name":"Siehl, Sebastian","last_name":"Siehl","first_name":"Sebastian"},{"full_name":"Nees, Frauke","first_name":"Frauke","last_name":"Nees"},{"first_name":"Argyris","last_name":"Stringaris","full_name":"Stringaris, Argyris"},{"full_name":"Tost, Heike","first_name":"Heike","last_name":"Tost"},{"full_name":"Meyer-Lindenberg, Andreas","first_name":"Andreas","last_name":"Meyer-Lindenberg"},{"last_name":"Christmann","first_name":"Nina","full_name":"Christmann, Nina"},{"first_name":"Jamie","last_name":"Banks","full_name":"Banks, Jamie"},{"full_name":"Schepanski, Kerstin","last_name":"Schepanski","first_name":"Kerstin"},{"full_name":"Schütz, Tatjana","first_name":"Tatjana","last_name":"Schütz"},{"last_name":"Taron","first_name":"Ulrike Helene","full_name":"Taron, Ulrike Helene"},{"first_name":"Roland","last_name":"Eils","full_name":"Eils, Roland"},{"full_name":"Roy, Jean Charles","first_name":"Jean Charles","last_name":"Roy"},{"last_name":"Lett","first_name":"Tristram A.","full_name":"Lett, Tristram A."},{"full_name":"Kebir, Hedi","first_name":"Hedi","last_name":"Kebir"},{"first_name":"Elli","last_name":"Polemiti","full_name":"Polemiti, Elli"},{"last_name":"Hitchen","first_name":"Esther","full_name":"Hitchen, Esther"},{"full_name":"Jentsch, Marcel","first_name":"Marcel","last_name":"Jentsch"},{"last_name":"Serin","first_name":"Emin","full_name":"Serin, Emin"},{"full_name":"Bernas, Antoine","last_name":"Bernas","first_name":"Antoine"},{"first_name":"Nilakshi","last_name":"Vaidya","full_name":"Vaidya, Nilakshi"},{"full_name":"Twardziok, Sven","first_name":"Sven","last_name":"Twardziok"},{"first_name":"Markus","last_name":"Ralser","full_name":"Ralser, Markus"},{"first_name":"Andreas","last_name":"Heinz","full_name":"Heinz, Andreas"}],"publication_status":"published","page":"1134-1137","title":"A protocol for data harmonization in large cohorts","doi":"10.1038/s44220-024-00315-0","OA_type":"closed access","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).","publisher":"Springer Nature","publication_identifier":{"eissn":["2731-6076"]},"abstract":[{"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.","lang":"eng"}],"scopus_import":"1","day":"01","volume":2,"month":"10","article_processing_charge":"No","publication":"Nature Mental Health","article_type":"comment","type":"journal_article","fulldoi":"https://doi.org/10.1038/s44220-024-00315-0","year":"2024","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","issue":"10"},{"OA_type":"free access","title":"A layered Bi2Te3@PPy cathode for aqueous Zinc‐Ion batteries: Mechanism and application in printed flexible batteries","doi":"10.1002/adma.202470004","date_published":"2024-01-04T00:00:00Z","author":[{"full_name":"Zeng, Guifang","last_name":"Zeng","first_name":"Guifang"},{"full_name":"Sun, Qing","last_name":"Sun","first_name":"Qing"},{"first_name":"Sharona","id":"03a7e858-01b1-11ec-8b71-99ae6c4a05bc","last_name":"Horta","full_name":"Horta, Sharona"},{"full_name":"Wang, Shang","last_name":"Wang","first_name":"Shang"},{"last_name":"Lu","first_name":"Xuan","full_name":"Lu, Xuan"},{"first_name":"Chao Yue","last_name":"Zhang","full_name":"Zhang, Chao Yue"},{"last_name":"Li","first_name":"Jing","full_name":"Li, Jing"},{"full_name":"Li, Junshan","first_name":"Junshan","last_name":"Li"},{"full_name":"Ci, Lijie","last_name":"Ci","first_name":"Lijie"},{"full_name":"Tian, Yanhong","last_name":"Tian","first_name":"Yanhong"},{"full_name":"Ibáñez, Maria","last_name":"Ibáñez","orcid":"0000-0001-5013-2843","id":"43C61214-F248-11E8-B48F-1D18A9856A87","first_name":"Maria"},{"full_name":"Cabot, Andreu","first_name":"Andreu","last_name":"Cabot"}],"publication_status":"published","status":"public","department":[{"_id":"MaIb"}],"main_file_link":[{"url":"https://doi.org/10.1002/adma.202470004","open_access":"1"}],"citation":{"ieee":"G. Zeng et al., A layered Bi2Te3@PPy cathode for aqueous Zinc‐Ion batteries: Mechanism and application in printed flexible batteries, vol. 36, no. 1. Wiley, 2024.","mla":"Zeng, Guifang, et al. “A Layered Bi2Te3@PPy Cathode for Aqueous Zinc‐Ion Batteries: Mechanism and Application in Printed Flexible Batteries.” Advanced Materials, vol. 36, no. 1, 2470004, Wiley, 2024, doi:10.1002/adma.202470004.","ama":"Zeng G, Sun Q, Horta S, et al. A Layered Bi2Te3@PPy Cathode for Aqueous Zinc‐Ion Batteries: Mechanism and Application in Printed Flexible Batteries. Vol 36. Wiley; 2024. doi:10.1002/adma.202470004","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.","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.","chicago":"Zeng, Guifang, Qing Sun, Sharona Horta, Shang Wang, Xuan Lu, Chao Yue Zhang, Jing Li, et al. A Layered Bi2Te3@PPy Cathode for Aqueous Zinc‐Ion Batteries: Mechanism and Application in Printed Flexible Batteries. Advanced Materials. Vol. 36. Wiley, 2024. https://doi.org/10.1002/adma.202470004.","apa":"Zeng, G., Sun, Q., Horta, S., Wang, S., Lu, X., Zhang, C. Y., … Cabot, A. (2024). A layered Bi2Te3@PPy cathode for aqueous Zinc‐Ion batteries: Mechanism and application in printed flexible batteries. Advanced Materials (Vol. 36). Wiley. https://doi.org/10.1002/adma.202470004"},"language":[{"iso":"eng"}],"oa_version":"Published Version","quality_controlled":"1","article_number":"2470004","date_updated":"2026-06-18T18:19:28Z","_id":"20057","intvolume":" 36","date_created":"2025-07-21T08:53:06Z","issue":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","fulldoi":"https://doi.org/10.1002/adma.202470004","year":"2024","type":"other_academic_publication","OA_place":"publisher","publication":"Advanced Materials","oa":1,"article_processing_charge":"No","month":"01","day":"04","volume":36,"publication_identifier":{"eissn":["1521-4095"],"issn":["0935-9648"]},"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"}],"publisher":"Wiley","ddc":["530"]},{"license":"https://creativecommons.org/licenses/by-nc-sa/4.0/","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","issue":"45","year":"2024","fulldoi":"https://doi.org/10.62876/lr.vi45.6481","PlanS_conform":"1","type":"journal_article","article_type":"original","article_processing_charge":"Yes","DOAJ_listed":"1","oa":1,"OA_place":"publisher","publication":"Lógoi. Revista de Filosofía","month":"03","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. \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_identifier":{"eissn":["1316-693X"],"issn":["2790-5144"]},"day":"19","ddc":["570"],"has_accepted_license":"1","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”.","corr_author":"1","publisher":"Universidad Católica Andrés Bello","OA_type":"gold","doi":"10.62876/lr.vi45.6481","file_date_updated":"2025-09-09T08:48:53Z","title":"Stuck in uncertainty: A predictive processing/ active inference account of procrastination-like behaviour in autism","page":"88-114","date_published":"2024-03-19T00:00:00Z","publication_status":"published","file":[{"file_size":354124,"content_type":"application/pdf","creator":"dernst","success":1,"date_created":"2025-09-09T08:48:53Z","relation":"main_file","checksum":"04c950f26ad68455c3a303c87ccf2349","date_updated":"2025-09-09T08:48:53Z","file_name":"2025_Logoi_CarlsDiamante.pdf","file_id":"20317","access_level":"open_access"}],"author":[{"full_name":"Carls-Diamante, Sidney","first_name":"Sidney","last_name":"Carls-Diamante"},{"first_name":"Alice","orcid":"0000-0002-5485-1391","last_name":"Laciny","id":"accace3f-3f77-11eb-b1df-f1221b04cb95","full_name":"Laciny, Alice"}],"citation":{"chicago":"Carls-Diamante, Sidney, and Alice Laciny. “Stuck in Uncertainty: A Predictive Processing/ Active Inference Account of Procrastination-like Behaviour in Autism.” Lógoi. Revista de Filosofía. Universidad Católica Andrés Bello, 2024. https://doi.org/10.62876/lr.vi45.6481.","apa":"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. Universidad Católica Andrés Bello. https://doi.org/10.62876/lr.vi45.6481","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. Lógoi Revista de Filosofía. 2024;(45):88-114. doi:10.62876/lr.vi45.6481","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.” Lógoi. Revista de Filosofía, no. 45, Universidad Católica Andrés Bello, 2024, pp. 88–114, doi:10.62876/lr.vi45.6481.","ieee":"S. Carls-Diamante and A. Laciny, “Stuck in uncertainty: A predictive processing/ active inference account of procrastination-like behaviour in autism,” Lógoi. Revista de Filosofía, no. 45. Universidad Católica Andrés Bello, pp. 88–114, 2024."},"status":"public","oa_version":"Published Version","language":[{"iso":"eng"}],"date_created":"2025-07-21T10:35:39Z","_id":"20060","tmp":{"image":"/images/cc_by_nc_sa.png","legal_code_url":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode","name":"Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","short":"CC BY-NC-SA (4.0)"},"date_updated":"2025-09-09T08:51:00Z","quality_controlled":"1"},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2024","fulldoi":"https://doi.org/10.5281/ZENODO.7137151","doi":"10.5281/ZENODO.7137151","title":"PyDaddy: A Python Package for Discovering SDEs from Time Series Data","type":"research_data_reference","date_published":"2024-09-18T00:00:00Z","author":[{"first_name":"Arshed","last_name":"Nabeel","full_name":"Nabeel, Arshed"},{"last_name":"Karichannavar","first_name":"Ashwin","full_name":"Karichannavar, Ashwin"},{"last_name":"Palathingal","first_name":"Shuaib","full_name":"Palathingal, Shuaib"},{"last_name":"Jhawar","first_name":"Jitesh","full_name":"Jhawar, Jitesh"},{"full_name":"Brückner, David","first_name":"David","id":"e1e86031-6537-11eb-953a-f7ab92be508d","last_name":"Brückner","orcid":"0000-0001-7205-2975"},{"last_name":"Danny Raj","first_name":"Masila","full_name":"Danny Raj, Masila"},{"first_name":"Vishwesha","last_name":"Guttal","full_name":"Guttal, Vishwesha"}],"citation":{"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. https://doi.org/10.5281/ZENODO.7137151.","apa":"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. https://doi.org/10.5281/ZENODO.7137151","short":"A. Nabeel, A. Karichannavar, S. Palathingal, J. Jhawar, D. Brückner, M. Danny Raj, V. Guttal, (2024).","mla":"Nabeel, Arshed, et al. PyDaddy: A Python Package for Discovering SDEs from Time Series Data. Zenodo, 2024, doi:10.5281/ZENODO.7137151.","ama":"Nabeel A, Karichannavar A, Palathingal S, et al. PyDaddy: A Python Package for Discovering SDEs from Time Series Data. 2024. doi:10.5281/ZENODO.7137151","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, 10.5281/ZENODO.7137151.","ieee":"A. Nabeel et al., “PyDaddy: A Python Package for Discovering SDEs from Time Series Data.” Zenodo, 2024."},"article_processing_charge":"No","main_file_link":[{"url":"https://doi.org/10.5281/zenodo.7137151","open_access":"1"}],"oa":1,"department":[{"_id":"EdHa"}],"status":"public","oa_version":"Published Version","month":"09","related_material":{"record":[{"id":"20056","status":"public","relation":"used_for_analysis_in"}]},"abstract":[{"lang":"eng","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."}],"date_created":"2025-08-05T06:49:59Z","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)"},"_id":"20121","date_updated":"2025-09-30T14:14:42Z","day":"18","ddc":["570"],"has_accepted_license":"1","acknowledgement":"This study was partially funded by Science and Engineering Research Board, Department of Science and Technology, Government of India to Vishwesha Guttal.","publisher":"Zenodo"},{"article_type":"comment","type":"journal_article","year":"2024","fulldoi":"https://doi.org/10.1038/s44220-024-00317-y","issue":"10","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","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.","publisher":"Springer Nature","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","publication_identifier":{"eissn":["2731-6076"]},"volume":2,"day":"01","month":"10","article_processing_charge":"No","publication":"Nature Mental Health","page":"1131-1133","publication_status":"published","date_published":"2024-10-01T00:00:00Z","author":[{"first_name":"Sylvane","last_name":"Desrivières","full_name":"Desrivières, Sylvane"},{"full_name":"Miller, Abigail","last_name":"Miller","first_name":"Abigail"},{"full_name":"Mathey, Carina M.","last_name":"Mathey","first_name":"Carina M."},{"full_name":"Yu, Xinyang","first_name":"Xinyang","last_name":"Yu"},{"full_name":"Chen, Di","last_name":"Chen","first_name":"Di"},{"last_name":"Agunbiade","first_name":"Kofoworola","full_name":"Agunbiade, Kofoworola"},{"last_name":"Heilmann-Heimbach","first_name":"Stefanie","full_name":"Heilmann-Heimbach, Stefanie"},{"last_name":"Forstner","first_name":"Andreas J.","full_name":"Forstner, Andreas J."},{"first_name":"Gunter","last_name":"Schumann","full_name":"Schumann, Gunter"},{"last_name":"Hoffmann","first_name":"Per","full_name":"Hoffmann, Per"},{"last_name":"Nöthen","first_name":"Markus M.","full_name":"Nöthen, Markus M."},{"first_name":"George","last_name":"Ogoh","full_name":"Ogoh, George"},{"full_name":"Stahl, Bernd","last_name":"Stahl","first_name":"Bernd"},{"full_name":"Young, Allan H.","last_name":"Young","first_name":"Allan H."},{"full_name":"Clinton, Nicholas","first_name":"Nicholas","last_name":"Clinton"},{"last_name":"Thompson","first_name":"Paul","full_name":"Thompson, Paul"},{"first_name":"Ameli","last_name":"Schwalber","full_name":"Schwalber, Ameli"},{"last_name":"Liu","first_name":"Jingyu","full_name":"Liu, Jingyu"},{"full_name":"Calhoun, Vince","first_name":"Vince","last_name":"Calhoun"},{"last_name":"Chang","first_name":"Xiao","full_name":"Chang, Xiao"},{"full_name":"Xia, Yunman","last_name":"Xia","first_name":"Yunman"},{"full_name":"Gong, Yanting","first_name":"Yanting","last_name":"Gong"},{"full_name":"Jia, Tianye","last_name":"Jia","first_name":"Tianye"},{"last_name":"Renner","first_name":"Paul","full_name":"Renner, Paul"},{"first_name":"Sören","last_name":"Hese","full_name":"Hese, Sören"},{"full_name":"Giner, Arantxa","last_name":"Giner","first_name":"Arantxa"},{"full_name":"Sanchez, Mavi","first_name":"Mavi","last_name":"Sanchez"},{"full_name":"Alvarez, Elena","last_name":"Alvarez","first_name":"Elena"},{"full_name":"Spanlang, Bernhard","last_name":"Spanlang","first_name":"Bernhard"},{"last_name":"Pearmund","first_name":"Charlie","full_name":"Pearmund, Charlie"},{"full_name":"Athanasiadis, Anastasios Polykarpos","last_name":"Athanasiadis","first_name":"Anastasios Polykarpos"},{"first_name":"Lisa","last_name":"Otten","full_name":"Otten, Lisa"},{"full_name":"Pitel, Séverine","last_name":"Pitel","first_name":"Séverine"},{"last_name":"Petkoski","first_name":"Spase","full_name":"Petkoski, Spase"},{"full_name":"Jirsa, Viktor","last_name":"Jirsa","first_name":"Viktor"},{"full_name":"Schmitt, Karen","last_name":"Schmitt","first_name":"Karen"},{"full_name":"Wilbertz, Johannes","last_name":"Wilbertz","first_name":"Johannes"},{"first_name":"Myrto","last_name":"Patraskaki","full_name":"Patraskaki, Myrto"},{"full_name":"Sommer, Peter","first_name":"Peter","last_name":"Sommer"},{"last_name":"Claus","first_name":"Isabelle","full_name":"Claus, Isabelle"},{"full_name":"Pastor, Alvaro","last_name":"Pastor","first_name":"Alvaro"},{"full_name":"Gallego, Jaime","last_name":"Gallego","first_name":"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"},{"first_name":"Lena","last_name":"Marr","id":"4406F586-F248-11E8-B48F-1D18A9856A87","full_name":"Marr, Lena"},{"full_name":"Novarino, Gaia","first_name":"Gaia","id":"3E57A680-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-7673-7178","last_name":"Novarino"},{"last_name":"Marquand","first_name":"Andre","full_name":"Marquand, Andre"},{"full_name":"Böttger, Sarah Jane","first_name":"Sarah Jane","last_name":"Böttger"},{"last_name":"Tschorn","first_name":"Mira","full_name":"Tschorn, Mira"},{"last_name":"Rapp","first_name":"Michael","full_name":"Rapp, Michael"},{"first_name":"Helga","last_name":"Ask","full_name":"Ask, Helga"},{"last_name":"Kjelkenes","first_name":"Rikka","full_name":"Kjelkenes, Rikka"},{"last_name":"Fernandez","first_name":"Sara","full_name":"Fernandez, Sara"},{"full_name":"Van Der Meer, Dennis","first_name":"Dennis","last_name":"Van Der Meer"},{"full_name":"Westlye, Lars T.","first_name":"Lars T.","last_name":"Westlye"},{"full_name":"Andreassen, Ole A.","last_name":"Andreassen","first_name":"Ole A."},{"last_name":"Aden","first_name":"Rieke","full_name":"Aden, Rieke"},{"full_name":"Seefried, Beke","last_name":"Seefried","first_name":"Beke"},{"full_name":"Siehl, Sebastian","last_name":"Siehl","first_name":"Sebastian"},{"last_name":"Nees","first_name":"Frauke","full_name":"Nees, Frauke"},{"first_name":"Maja","last_name":"Neidhart","full_name":"Neidhart, Maja"},{"first_name":"Argyris","last_name":"Stringaris","full_name":"Stringaris, Argyris"},{"first_name":"Emanuel","last_name":"Schwarz","full_name":"Schwarz, Emanuel"},{"full_name":"Holz, Nathalie","first_name":"Nathalie","last_name":"Holz"},{"full_name":"Tost, Heike","first_name":"Heike","last_name":"Tost"},{"last_name":"Meyer-Lindenberg","first_name":"Andreas","full_name":"Meyer-Lindenberg, Andreas"},{"last_name":"Christmann","first_name":"Nina","full_name":"Christmann, Nina"},{"full_name":"Jansone, Karina","first_name":"Karina","last_name":"Jansone"},{"first_name":"Tobias","last_name":"Banaschewski","full_name":"Banaschewski, Tobias"},{"first_name":"Jamie","last_name":"Banks","full_name":"Banks, Jamie"},{"full_name":"Schepanski, Kerstin","last_name":"Schepanski","first_name":"Kerstin"},{"full_name":"Schütz, Tatjana","first_name":"Tatjana","last_name":"Schütz"},{"full_name":"Taron, Ulrike Helene","last_name":"Taron","first_name":"Ulrike Helene"},{"full_name":"Eils, Roland","last_name":"Eils","first_name":"Roland"},{"full_name":"Roy, Jean Charles","last_name":"Roy","first_name":"Jean Charles"},{"full_name":"Lett, Tristram A.","last_name":"Lett","first_name":"Tristram A."},{"full_name":"Kebir, Hedi","first_name":"Hedi","last_name":"Kebir"},{"last_name":"Polemiti","first_name":"Elli","full_name":"Polemiti, Elli"},{"first_name":"Esther","last_name":"Hitchen","full_name":"Hitchen, Esther"},{"full_name":"Jentsch, Marcel","first_name":"Marcel","last_name":"Jentsch"},{"full_name":"Serin, Emin","first_name":"Emin","last_name":"Serin"},{"last_name":"Bernas","first_name":"Antoine","full_name":"Bernas, Antoine"},{"first_name":"Nilakshi","last_name":"Vaidya","full_name":"Vaidya, Nilakshi"},{"first_name":"Sven","last_name":"Twardziok","full_name":"Twardziok, Sven"},{"last_name":"Ralser","first_name":"Markus","full_name":"Ralser, Markus"},{"full_name":"Heinz, Andreas","last_name":"Heinz","first_name":"Andreas"},{"full_name":"Walter, Henrik","first_name":"Henrik","last_name":"Walter"}],"doi":"10.1038/s44220-024-00317-y","title":"Multi-omics analyses of the environMENTAL project provide insights into mental health and disease","OA_type":"closed access","date_created":"2025-08-10T22:01:30Z","intvolume":" 2","_id":"20156","date_updated":"2025-08-11T06:44:03Z","quality_controlled":"1","oa_version":"None","language":[{"iso":"eng"}],"citation":{"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.","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. Nature Mental Health. Springer Nature. https://doi.org/10.1038/s44220-024-00317-y","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.” Nature Mental Health. Springer Nature, 2024. https://doi.org/10.1038/s44220-024-00317-y.","ieee":"S. Desrivières et al., “Multi-omics analyses of the environMENTAL project provide insights into mental health and disease,” Nature Mental Health, vol. 2, no. 10. Springer Nature, pp. 1131–1133, 2024.","ama":"Desrivières S, Miller A, Mathey CM, et al. Multi-omics analyses of the environMENTAL project provide insights into mental health and disease. Nature Mental Health. 2024;2(10):1131-1133. doi:10.1038/s44220-024-00317-y","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.","mla":"Desrivières, Sylvane, et al. “Multi-Omics Analyses of the EnvironMENTAL Project Provide Insights into Mental Health and Disease.” Nature Mental Health, vol. 2, no. 10, Springer Nature, 2024, pp. 1131–33, doi:10.1038/s44220-024-00317-y."},"department":[{"_id":"GaNo"}],"status":"public"},{"issue":"10","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2024","fulldoi":"https://doi.org/10.1038/s44220-024-00320-3","type":"journal_article","article_type":"comment","publication":"Nature Mental Health","article_processing_charge":"No","month":"10","volume":2,"day":"01","scopus_import":"1","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"}],"publication_identifier":{"eissn":["2731-6076"]},"publisher":"Springer Nature","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).","OA_type":"closed access","doi":"10.1038/s44220-024-00320-3","title":"Rethinking ethics in interdisciplinary and big data-driven neuroscience projects","date_published":"2024-10-01T00:00:00Z","publication_status":"published","author":[{"full_name":"Stahl, Bernd","first_name":"Bernd","last_name":"Stahl"},{"first_name":"George","last_name":"Ogoh","full_name":"Ogoh, George"},{"full_name":"Schumann, Gunter","first_name":"Gunter","last_name":"Schumann"},{"full_name":"Walter, Henrik","last_name":"Walter","first_name":"Henrik"},{"last_name":"Stahl","first_name":"Bernd","full_name":"Stahl, Bernd"},{"full_name":"Young, Allan H.","first_name":"Allan H.","last_name":"Young"},{"full_name":"Desrivières, Sylvane","last_name":"Desrivières","first_name":"Sylvane"},{"full_name":"Clinton, Nicholas","last_name":"Clinton","first_name":"Nicholas"},{"last_name":"Thompson","first_name":"Paul","full_name":"Thompson, Paul"},{"full_name":"Schwalber, Ameli","last_name":"Schwalber","first_name":"Ameli"},{"full_name":"Liu, Jingyu","last_name":"Liu","first_name":"Jingyu"},{"last_name":"Calhoun","first_name":"Vince","full_name":"Calhoun, Vince"},{"full_name":"Chang, Xiao","last_name":"Chang","first_name":"Xiao"},{"first_name":"Yunman","last_name":"Xia","full_name":"Xia, Yunman"},{"first_name":"Yanting","last_name":"Gong","full_name":"Gong, Yanting"},{"full_name":"Jia, Tianye","first_name":"Tianye","last_name":"Jia"},{"first_name":"Paul","last_name":"Renner","full_name":"Renner, Paul"},{"first_name":"Sören","last_name":"Hese","full_name":"Hese, Sören"},{"full_name":"Giner, Arantxa","first_name":"Arantxa","last_name":"Giner"},{"full_name":"Sanchez, Mavi","first_name":"Mavi","last_name":"Sanchez"},{"full_name":"Alvarez, Elena","first_name":"Elena","last_name":"Alvarez"},{"full_name":"Spanlang, Bernhard","first_name":"Bernhard","last_name":"Spanlang"},{"full_name":"Pearmund, Charlie","first_name":"Charlie","last_name":"Pearmund"},{"last_name":"Athanasiadis","first_name":"Anastasios Polykarpos","full_name":"Athanasiadis, Anastasios Polykarpos"},{"full_name":"Otten, Lisa","first_name":"Lisa","last_name":"Otten"},{"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","last_name":"Schmitt","full_name":"Schmitt, Karen"},{"last_name":"Wilbertz","first_name":"Johannes","full_name":"Wilbertz, Johannes"},{"full_name":"Patraskaki, Myrto","last_name":"Patraskaki","first_name":"Myrto"},{"full_name":"Sommer, Peter","first_name":"Peter","last_name":"Sommer"},{"full_name":"Heilmann-Heimbach, Stefanie","first_name":"Stefanie","last_name":"Heilmann-Heimbach"},{"full_name":"Mathey, Carina M.","first_name":"Carina M.","last_name":"Mathey"},{"full_name":"Miller, Abigail","last_name":"Miller","first_name":"Abigail"},{"full_name":"Claus, Isabelle","first_name":"Isabelle","last_name":"Claus"},{"last_name":"Nöthen","first_name":"Markus M.","full_name":"Nöthen, Markus M."},{"full_name":"Hoffmann, Per","first_name":"Per","last_name":"Hoffmann"},{"first_name":"Andreas J.","last_name":"Forstner","full_name":"Forstner, Andreas J."},{"full_name":"Pastor, Alvaro","first_name":"Alvaro","last_name":"Pastor"},{"first_name":"Jaime","last_name":"Gallego","full_name":"Gallego, Jaime"},{"full_name":"Orosa, Francisco Eiroa","first_name":"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","first_name":"Gaia","id":"3E57A680-F248-11E8-B48F-1D18A9856A87","last_name":"Novarino","orcid":"0000-0002-7673-7178"},{"full_name":"Marquand, Andre","last_name":"Marquand","first_name":"Andre"},{"full_name":"Böttger, Sarah Jane","first_name":"Sarah Jane","last_name":"Böttger"},{"full_name":"Tschorn, Mira","first_name":"Mira","last_name":"Tschorn"},{"full_name":"Rapp, Michael","first_name":"Michael","last_name":"Rapp"},{"full_name":"Ask, Helga","last_name":"Ask","first_name":"Helga"},{"full_name":"Kjelkenes, Rikka","first_name":"Rikka","last_name":"Kjelkenes"},{"last_name":"Fernandez","first_name":"Sara","full_name":"Fernandez, Sara"},{"first_name":"Dennis","last_name":"Van Der Meer","full_name":"Van Der Meer, Dennis"},{"full_name":"Westlye, Lars T.","first_name":"Lars T.","last_name":"Westlye"},{"full_name":"Andreassen, Ole A.","first_name":"Ole A.","last_name":"Andreassen"},{"full_name":"Aden, Rieke","last_name":"Aden","first_name":"Rieke"},{"full_name":"Seefried, Beke","first_name":"Beke","last_name":"Seefried"},{"full_name":"Siehl, Sebastian","last_name":"Siehl","first_name":"Sebastian"},{"first_name":"Frauke","last_name":"Nees","full_name":"Nees, Frauke"},{"full_name":"Neidhart, Maja","first_name":"Maja","last_name":"Neidhart"},{"first_name":"Argyris","last_name":"Stringaris","full_name":"Stringaris, Argyris"},{"first_name":"Emanuel","last_name":"Schwarz","full_name":"Schwarz, Emanuel"},{"first_name":"Nathalie","last_name":"Holz","full_name":"Holz, Nathalie"},{"full_name":"Tost, Heike","first_name":"Heike","last_name":"Tost"},{"last_name":"Meyer-Lindenberg","first_name":"Andreas","full_name":"Meyer-Lindenberg, Andreas"},{"full_name":"Christmann, Nina","last_name":"Christmann","first_name":"Nina"},{"full_name":"Jansone, Karina","first_name":"Karina","last_name":"Jansone"},{"last_name":"Banaschewski","first_name":"Tobias","full_name":"Banaschewski, Tobias"},{"first_name":"Jamie","last_name":"Banks","full_name":"Banks, Jamie"},{"first_name":"Kerstin","last_name":"Schepanski","full_name":"Schepanski, Kerstin"},{"full_name":"Schütz, Tatjana","first_name":"Tatjana","last_name":"Schütz"},{"first_name":"Ulrike Helene","last_name":"Taron","full_name":"Taron, Ulrike Helene"},{"first_name":"Roland","last_name":"Eils","full_name":"Eils, Roland"},{"full_name":"Roy, Jean Charles","last_name":"Roy","first_name":"Jean Charles"},{"full_name":"Lett, Tristram A.","last_name":"Lett","first_name":"Tristram A."},{"first_name":"Hedi","last_name":"Kebir","full_name":"Kebir, Hedi"},{"full_name":"Polemiti, Elli","first_name":"Elli","last_name":"Polemiti"},{"full_name":"Hitchen, Esther","first_name":"Esther","last_name":"Hitchen"},{"last_name":"Jentsch","first_name":"Marcel","full_name":"Jentsch, Marcel"},{"full_name":"Serin, Emin","first_name":"Emin","last_name":"Serin"},{"full_name":"Bernas, Antoine","first_name":"Antoine","last_name":"Bernas"},{"first_name":"Nilakshi","last_name":"Vaidya","full_name":"Vaidya, Nilakshi"},{"last_name":"Twardziok","first_name":"Sven","full_name":"Twardziok, Sven"},{"first_name":"Markus","last_name":"Ralser","full_name":"Ralser, Markus"},{"full_name":"Heinz, Andreas","first_name":"Andreas","last_name":"Heinz"},{"full_name":"Walter, Henrik","last_name":"Walter","first_name":"Henrik"}],"status":"public","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. Nature Mental Health. Springer Nature. https://doi.org/10.1038/s44220-024-00320-3","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.” Nature Mental Health. Springer Nature, 2024. https://doi.org/10.1038/s44220-024-00320-3.","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).","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.","ama":"Stahl B, Ogoh G, Schumann G, et al. Rethinking ethics in interdisciplinary and big data-driven neuroscience projects. Nature Mental Health. 2024;2(10). doi:10.1038/s44220-024-00320-3","mla":"Stahl, Bernd, et al. “Rethinking Ethics in Interdisciplinary and Big Data-Driven Neuroscience Projects.” Nature Mental Health, vol. 2, no. 10, 1128–1130, Springer Nature, 2024, doi:10.1038/s44220-024-00320-3.","ieee":"B. Stahl et al., “Rethinking ethics in interdisciplinary and big data-driven neuroscience projects,” Nature Mental Health, vol. 2, no. 10. Springer Nature, 2024."},"department":[{"_id":"GaNo"}],"language":[{"iso":"eng"}],"oa_version":"None","_id":"20157","date_updated":"2025-08-11T06:53:55Z","quality_controlled":"1","article_number":"1128-1130","date_created":"2025-08-10T22:01:30Z","intvolume":" 2"}]