[{"author":[{"last_name":"Xu","first_name":"Danru","full_name":"Xu, Danru"},{"full_name":"Yao, Dingling","id":"d3e02e50-48a8-11ee-8f62-c108061797fa","first_name":"Dingling","last_name":"Yao"},{"full_name":"Lachapelle, Sebastien","last_name":"Lachapelle","first_name":"Sebastien"},{"full_name":"Taslakian, Perouz","last_name":"Taslakian","first_name":"Perouz"},{"full_name":"von Kügelgen, Julius","last_name":"von Kügelgen","first_name":"Julius"},{"full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco","last_name":"Locatello"},{"full_name":"Magliacane, Sara","last_name":"Magliacane","first_name":"Sara"}],"abstract":[{"lang":"eng","text":"Causal representation learning (CRL) aims at identifying high-level causal variables from low-level data, e.g. images. Current methods usually assume that all causal variables are captured in the high-dimensional observations. In this work, we focus on learning causal representations from data under partial observability, i.e., when some of the causal variables are not observed in the measurements, and the set of masked variables changes across the different samples. We introduce some initial theoretical results for identifying causal variables under partial observability by exploiting a sparsity regularizer, focusing in particular on the linear and piecewise linear mixing function case. We provide a theorem that allows us to identify the causal variables up to permutation and element-wise linear transformations in the linear case and a lemma that allows us to identify causal variables up to linear transformation in the piecewise case. Finally, we provide a conjecture that would allow us to identify the causal variables up to permutation and element-wise linear transformations also in the piecewise linear case. We test the theorem and conjecture on simulated data, showing the effectiveness of our method."}],"department":[{"_id":"FrLo"}],"_id":"14958","oa_version":"Published Version","oa":1,"file":[{"creator":"dernst","success":1,"date_created":"2024-02-13T08:50:53Z","checksum":"484efc27bda75ed6666044989695d9b6","access_level":"open_access","date_updated":"2024-02-13T08:50:53Z","file_size":552357,"content_type":"application/pdf","file_id":"14982","relation":"main_file","file_name":"2023_CRL_Xu.pdf"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2023","publication_status":"published","date_updated":"2025-02-04T12:37:34Z","file_date_updated":"2024-02-13T08:50:53Z","publication":"Causal Representation Learning Workshop at NeurIPS 2023","article_processing_charge":"No","quality_controlled":"1","language":[{"iso":"eng"}],"publisher":"OpenReview","OA_place":"repository","license":"https://creativecommons.org/licenses/by/4.0/","month":"12","article_number":"54","tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"conference":{"name":"CRL: Causal Representation Learning Workshop at NeurIPS","end_date":"2023-12-15","location":"New Orleans, LA, United States","start_date":"2023-12-15"},"date_published":"2023-12-05T00:00:00Z","citation":{"ista":"Xu D, Yao D, Lachapelle S, Taslakian P, von Kügelgen J, Locatello F, Magliacane S. 2023. A sparsity principle for partially observable causal representation learning. Causal Representation Learning Workshop at NeurIPS 2023. CRL: Causal Representation Learning Workshop at NeurIPS, 54.","apa":"Xu, D., Yao, D., Lachapelle, S., Taslakian, P., von Kügelgen, J., Locatello, F., &#38; Magliacane, S. (2023). A sparsity principle for partially observable causal representation learning. In <i>Causal Representation Learning Workshop at NeurIPS 2023</i>. New Orleans, LA, United States: OpenReview.","short":"D. Xu, D. Yao, S. Lachapelle, P. Taslakian, J. von Kügelgen, F. Locatello, S. Magliacane, in:, Causal Representation Learning Workshop at NeurIPS 2023, OpenReview, 2023.","chicago":"Xu, Danru, Dingling Yao, Sebastien Lachapelle, Perouz Taslakian, Julius von Kügelgen, Francesco Locatello, and Sara Magliacane. “A Sparsity Principle for Partially Observable Causal Representation Learning.” In <i>Causal Representation Learning Workshop at NeurIPS 2023</i>. OpenReview, 2023.","ieee":"D. Xu <i>et al.</i>, “A sparsity principle for partially observable causal representation learning,” in <i>Causal Representation Learning Workshop at NeurIPS 2023</i>, New Orleans, LA, United States, 2023.","ama":"Xu D, Yao D, Lachapelle S, et al. A sparsity principle for partially observable causal representation learning. In: <i>Causal Representation Learning Workshop at NeurIPS 2023</i>. OpenReview; 2023.","mla":"Xu, Danru, et al. “A Sparsity Principle for Partially Observable Causal Representation Learning.” <i>Causal Representation Learning Workshop at NeurIPS 2023</i>, 54, OpenReview, 2023."},"status":"public","has_accepted_license":"1","date_created":"2024-02-07T15:17:51Z","main_file_link":[{"open_access":"1","url":"https://openreview.net/forum?id=Whr6uobelR"}],"acknowledgement":"This work was initiated at the Second Bellairs Workshop on Causality held at the Bellairs Research Institute, January 6–13, 2022; we thank all workshop participants for providing a stimulating research environment. The research of DX and SM was supported by the Air Force Office of Scientific Research under award number FA8655-22-1-7155. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the United States Air Force. We also thank SURF for the support in using the Dutch National Supercomputer Snellius. DY was supported by an Amazon fellowship and the International Max Planck Research School for Intelligent Systems (IMPRS-IS). Work done outside of Amazon. SL was supported by an IVADO excellence PhD scholarship and by Samsung Electronics Co., Ldt. JvK acknowledges support from the German Federal Ministry of Education and Research (BMBF)\r\nthrough the Tübingen AI Center (FKZ: 01IS18039B).\r\n","type":"conference","day":"05","OA_type":"green","title":"A sparsity principle for partially observable causal representation learning","ddc":["000"]},{"title":"Shortcuts for causal discovery of nonlinear models by score matching","date_updated":"2024-10-09T21:08:10Z","corr_author":"1","date_created":"2024-02-08T15:31:46Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","arxiv":1,"doi":"10.48550/arXiv.2310.14246","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2310.14246","open_access":"1"}],"status":"public","publication_status":"submitted","type":"preprint","day":"22","year":"2023","oa_version":"Preprint","_id":"14961","article_number":"2310.14246","citation":{"apa":"Montagna, F., Noceti, N., Rosasco, L., &#38; Locatello, F. (n.d.). Shortcuts for causal discovery of nonlinear models by score matching. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2310.14246\">https://doi.org/10.48550/arXiv.2310.14246</a>","ista":"Montagna F, Noceti N, Rosasco L, Locatello F. Shortcuts for causal discovery of nonlinear models by score matching. arXiv, 2310.14246.","short":"F. Montagna, N. Noceti, L. Rosasco, F. Locatello, ArXiv (n.d.).","ama":"Montagna F, Noceti N, Rosasco L, Locatello F. Shortcuts for causal discovery of nonlinear models by score matching. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2310.14246\">10.48550/arXiv.2310.14246</a>","chicago":"Montagna, Francesco, Nicoletta Noceti, Lorenzo Rosasco, and Francesco Locatello. “Shortcuts for Causal Discovery of Nonlinear Models by Score Matching.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2310.14246\">https://doi.org/10.48550/arXiv.2310.14246</a>.","ieee":"F. Montagna, N. Noceti, L. Rosasco, and F. Locatello, “Shortcuts for causal discovery of nonlinear models by score matching,” <i>arXiv</i>. .","mla":"Montagna, Francesco, et al. “Shortcuts for Causal Discovery of Nonlinear Models by Score Matching.” <i>ArXiv</i>, 2310.14246, doi:<a href=\"https://doi.org/10.48550/arXiv.2310.14246\">10.48550/arXiv.2310.14246</a>."},"oa":1,"date_published":"2023-10-22T00:00:00Z","abstract":[{"text":"The use of simulated data in the field of causal discovery is ubiquitous due to the scarcity of annotated real data. Recently, Reisach et al., 2021 highlighted the emergence of patterns in simulated linear data, which displays increasing marginal variance in the casual direction. As an ablation in their experiments, Montagna et al., 2023 found that similar patterns may emerge in\r\nnonlinear models for the variance of the score vector $\\nabla \\log p_{\\mathbf{X}}$, and introduced the ScoreSort algorithm. In this work, we formally define and characterize this score-sortability pattern of nonlinear additive noise models. We find that it defines a class of identifiable (bivariate) causal models overlapping with nonlinear additive noise models. We\r\ntheoretically demonstrate the advantages of ScoreSort in terms of statistical efficiency compared to prior state-of-the-art score matching-based methods and empirically show the score-sortability of the most common synthetic benchmarks in the literature. Our findings remark (1) the lack of diversity in the data as an important limitation in the evaluation of nonlinear causal discovery approaches, (2) the importance of thoroughly testing different settings within a problem class, and (3) the importance of analyzing statistical properties in\r\ncausal discovery, where research is often limited to defining identifiability conditions of the model. ","lang":"eng"}],"article_processing_charge":"No","publication":"arXiv","external_id":{"arxiv":["2310.14246"]},"author":[{"full_name":"Montagna, Francesco","last_name":"Montagna","first_name":"Francesco"},{"full_name":"Noceti, Nicoletta","first_name":"Nicoletta","last_name":"Noceti"},{"first_name":"Lorenzo","last_name":"Rosasco","full_name":"Rosasco, Lorenzo"},{"first_name":"Francesco","last_name":"Locatello","full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4"}],"month":"10","department":[{"_id":"FrLo"}],"language":[{"iso":"eng"}]},{"date_created":"2024-02-08T15:33:39Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","arxiv":1,"doi":"10.48550/arXiv.2309.09858","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2309.09858","open_access":"1"}],"status":"public","publication_status":"submitted","day":"18","type":"preprint","year":"2023","title":"Unsupervised open-vocabulary object localization in videos","date_updated":"2024-02-12T10:12:22Z","abstract":[{"text":"In this paper, we show that recent advances in video representation learning\r\nand pre-trained vision-language models allow for substantial improvements in\r\nself-supervised video object localization. We propose a method that first\r\nlocalizes objects in videos via a slot attention approach and then assigns text\r\nto the obtained slots. The latter is achieved by an unsupervised way to read\r\nlocalized semantic information from the pre-trained CLIP model. The resulting\r\nvideo object localization is entirely unsupervised apart from the implicit\r\nannotation contained in CLIP, and it is effectively the first unsupervised\r\napproach that yields good results on regular video benchmarks.","lang":"eng"}],"extern":"1","article_processing_charge":"No","publication":"arXiv","external_id":{"arxiv":["2309.09858"]},"author":[{"full_name":"Fan, Ke","first_name":"Ke","last_name":"Fan"},{"first_name":"Zechen","last_name":"Bai","full_name":"Bai, Zechen"},{"first_name":"Tianjun","last_name":"Xiao","full_name":"Xiao, Tianjun"},{"last_name":"Zietlow","first_name":"Dominik","full_name":"Zietlow, Dominik"},{"full_name":"Horn, Max","last_name":"Horn","first_name":"Max"},{"last_name":"Zhao","first_name":"Zixu","full_name":"Zhao, Zixu"},{"full_name":"Carl-Johann Simon-Gabriel, Carl-Johann Simon-Gabriel","last_name":"Carl-Johann Simon-Gabriel","first_name":"Carl-Johann Simon-Gabriel"},{"first_name":"Mike Zheng","last_name":"Shou","full_name":"Shou, Mike Zheng"},{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco","last_name":"Locatello","first_name":"Francesco"},{"last_name":"Schiele","first_name":"Bernt","full_name":"Schiele, Bernt"},{"full_name":"Brox, Thomas","last_name":"Brox","first_name":"Thomas"},{"full_name":"Zhang, Zheng","first_name":"Zheng","last_name":"Zhang"},{"last_name":"Fu","first_name":"Yanwei","full_name":"Fu, Yanwei"},{"full_name":"He, Tong","first_name":"Tong","last_name":"He"}],"department":[{"_id":"FrLo"}],"month":"09","language":[{"iso":"eng"}],"oa_version":"Preprint","article_number":"2309.09858","_id":"14962","citation":{"apa":"Fan, K., Bai, Z., Xiao, T., Zietlow, D., Horn, M., Zhao, Z., … He, T. (n.d.). Unsupervised open-vocabulary object localization in videos. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2309.09858\">https://doi.org/10.48550/arXiv.2309.09858</a>","ista":"Fan K, Bai Z, Xiao T, Zietlow D, Horn M, Zhao Z, Carl-Johann Simon-Gabriel C-JS-G, Shou MZ, Locatello F, Schiele B, Brox T, Zhang Z, Fu Y, He T. Unsupervised open-vocabulary object localization in videos. arXiv, 2309.09858.","short":"K. Fan, Z. Bai, T. Xiao, D. Zietlow, M. Horn, Z. Zhao, C.-J.S.-G. Carl-Johann Simon-Gabriel, M.Z. Shou, F. Locatello, B. Schiele, T. Brox, Z. Zhang, Y. Fu, T. He, ArXiv (n.d.).","ama":"Fan K, Bai Z, Xiao T, et al. Unsupervised open-vocabulary object localization in videos. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2309.09858\">10.48550/arXiv.2309.09858</a>","chicago":"Fan, Ke, Zechen Bai, Tianjun Xiao, Dominik Zietlow, Max Horn, Zixu Zhao, Carl-Johann Simon-Gabriel Carl-Johann Simon-Gabriel, et al. “Unsupervised Open-Vocabulary Object Localization in Videos.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2309.09858\">https://doi.org/10.48550/arXiv.2309.09858</a>.","ieee":"K. Fan <i>et al.</i>, “Unsupervised open-vocabulary object localization in videos,” <i>arXiv</i>. .","mla":"Fan, Ke, et al. “Unsupervised Open-Vocabulary Object Localization in Videos.” <i>ArXiv</i>, 2309.09858, doi:<a href=\"https://doi.org/10.48550/arXiv.2309.09858\">10.48550/arXiv.2309.09858</a>."},"oa":1,"date_published":"2023-09-18T00:00:00Z"},{"date_published":"2023-09-01T00:00:00Z","oa":1,"citation":{"chicago":"Zhao, Zixu, Jiaze Wang, Max Horn, Yizhuo Ding, Tong He, Zechen Bai, Dominik Zietlow, et al. “Object-Centric Multiple Object Tracking.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2309.00233\">https://doi.org/10.48550/arXiv.2309.00233</a>.","ieee":"Z. Zhao <i>et al.</i>, “Object-centric multiple object tracking,” <i>arXiv</i>. .","ama":"Zhao Z, Wang J, Horn M, et al. Object-centric multiple object tracking. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2309.00233\">10.48550/arXiv.2309.00233</a>","mla":"Zhao, Zixu, et al. “Object-Centric Multiple Object Tracking.” <i>ArXiv</i>, 2309.00233, doi:<a href=\"https://doi.org/10.48550/arXiv.2309.00233\">10.48550/arXiv.2309.00233</a>.","ista":"Zhao Z, Wang J, Horn M, Ding Y, He T, Bai Z, Zietlow D, Carl-Johann Simon-Gabriel C-JS-G, Shuai B, Tu Z, Brox T, Schiele B, Fu Y, Locatello F, Zhang Z, Xiao T. Object-centric multiple object tracking. arXiv, 2309.00233.","apa":"Zhao, Z., Wang, J., Horn, M., Ding, Y., He, T., Bai, Z., … Xiao, T. (n.d.). Object-centric multiple object tracking. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2309.00233\">https://doi.org/10.48550/arXiv.2309.00233</a>","short":"Z. Zhao, J. Wang, M. Horn, Y. Ding, T. He, Z. Bai, D. Zietlow, C.-J.S.-G. Carl-Johann Simon-Gabriel, B. Shuai, Z. Tu, T. Brox, B. Schiele, Y. Fu, F. Locatello, Z. Zhang, T. Xiao, ArXiv (n.d.)."},"oa_version":"Preprint","_id":"14963","article_number":"2309.00233","month":"09","department":[{"_id":"FrLo"}],"language":[{"iso":"eng"}],"article_processing_charge":"No","extern":"1","abstract":[{"lang":"eng","text":"Unsupervised object-centric learning methods allow the partitioning of scenes\r\ninto entities without additional localization information and are excellent\r\ncandidates for reducing the annotation burden of multiple-object tracking (MOT)\r\npipelines. Unfortunately, they lack two key properties: objects are often split\r\ninto parts and are not consistently tracked over time. In fact,\r\nstate-of-the-art models achieve pixel-level accuracy and temporal consistency\r\nby relying on supervised object detection with additional ID labels for the\r\nassociation through time. This paper proposes a video object-centric model for\r\nMOT. It consists of an index-merge module that adapts the object-centric slots\r\ninto detection outputs and an object memory module that builds complete object\r\nprototypes to handle occlusions. Benefited from object-centric learning, we\r\nonly require sparse detection labels (0%-6.25%) for object localization and\r\nfeature binding. Relying on our self-supervised\r\nExpectation-Maximization-inspired loss for object association, our approach\r\nrequires no ID labels. Our experiments significantly narrow the gap between the\r\nexisting object-centric model and the fully supervised state-of-the-art and\r\noutperform several unsupervised trackers."}],"author":[{"first_name":"Zixu","last_name":"Zhao","full_name":"Zhao, Zixu"},{"full_name":"Wang, Jiaze","first_name":"Jiaze","last_name":"Wang"},{"full_name":"Horn, Max","first_name":"Max","last_name":"Horn"},{"full_name":"Ding, Yizhuo","first_name":"Yizhuo","last_name":"Ding"},{"full_name":"He, Tong","last_name":"He","first_name":"Tong"},{"full_name":"Bai, Zechen","first_name":"Zechen","last_name":"Bai"},{"first_name":"Dominik","last_name":"Zietlow","full_name":"Zietlow, Dominik"},{"full_name":"Carl-Johann Simon-Gabriel, Carl-Johann Simon-Gabriel","last_name":"Carl-Johann Simon-Gabriel","first_name":"Carl-Johann Simon-Gabriel"},{"full_name":"Shuai, Bing","last_name":"Shuai","first_name":"Bing"},{"last_name":"Tu","first_name":"Zhuowen","full_name":"Tu, Zhuowen"},{"last_name":"Brox","first_name":"Thomas","full_name":"Brox, Thomas"},{"full_name":"Schiele, Bernt","last_name":"Schiele","first_name":"Bernt"},{"full_name":"Fu, Yanwei","last_name":"Fu","first_name":"Yanwei"},{"orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco","last_name":"Locatello"},{"full_name":"Zhang, Zheng","last_name":"Zhang","first_name":"Zheng"},{"first_name":"Tianjun","last_name":"Xiao","full_name":"Xiao, Tianjun"}],"external_id":{"arxiv":["2309.00233"]},"publication":"arXiv","title":"Object-centric multiple object tracking","date_updated":"2024-02-12T10:16:21Z","type":"preprint","day":"01","publication_status":"submitted","year":"2023","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","doi":"10.48550/arXiv.2309.00233","main_file_link":[{"url":" https://doi.org/10.48550/arXiv.2309.00233","open_access":"1"}],"arxiv":1,"date_created":"2024-02-08T15:34:43Z","status":"public"},{"publication_date":"2023-05-25","_id":"14965","oa_version":"Published Version","page":"9","ipc":"C12Q1/68 ; G06V10/82 ; G06V20/69 ; G16B40/30","oa":1,"author":[{"last_name":"Ficek","first_name":"Joanna","full_name":"Ficek, Joanna"},{"full_name":"Lehmann, Kjong-Van","first_name":"Kjong-Van","last_name":"Lehmann"},{"orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco","last_name":"Locatello"},{"full_name":"Raetsch, Gunnar ","first_name":"Gunnar ","last_name":"Raetsch"},{"first_name":"Stefan","last_name":"Stark","full_name":"Stark, Stefan"}],"extern":"1","abstract":[{"text":"A method of determining a correspondence between a first biological property of a cell and one or more further biological properties of cells is provided. The first biological property and the further biological properties are determined by different analysis techniques and each are contained in a respective one of a plurality of sets of biological properties. The method includes the steps of: converting the plurality of sets of biological properties into corresponding representations in a representation format which is invariant to the technologies used to derive the biological properties; determining, in said representation format, a representation from each of the converted sets of further biological properties which most closely matches the first representation of the first biological property; and re-converting the determined representations from the representation format back to the biological properties associated with the determined representations and thereby determining a correspondence between the first biological property and each of the further biological properties.","lang":"eng"}],"application_number":"PCT/EP2021/060318","department":[{"_id":"FrLo"}],"date_updated":"2025-01-29T10:53:48Z","file_date_updated":"2024-02-08T15:41:51Z","file":[{"checksum":"55ed444b176b48e4fb4d609ea895de36","date_created":"2024-02-08T15:41:51Z","success":1,"creator":"ptazenko","access_level":"open_access","relation":"main_file","file_id":"14966","content_type":"application/pdf","date_updated":"2024-02-08T15:41:51Z","file_size":2893462,"file_name":"Patent_FrLo_US20230162818A1.pdf"}],"ipn":"US20230162818A1","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","year":"2023","citation":{"mla":"Ficek, Joanna, et al. <i>Methods of Determining Correspondences between Biological Properties of Cells</i>. 2023.","ama":"Ficek J, Lehmann K-V, Locatello F, Raetsch G, Stark S. Methods of determining correspondences between biological properties of cells. 2023.","chicago":"Ficek, Joanna, Kjong-Van Lehmann, Francesco Locatello, Gunnar  Raetsch, and Stefan Stark. “Methods of Determining Correspondences between Biological Properties of Cells,” 2023.","ieee":"J. Ficek, K.-V. Lehmann, F. Locatello, G. Raetsch, and S. Stark, “Methods of determining correspondences between biological properties of cells.” 2023.","short":"J. Ficek, K.-V. Lehmann, F. Locatello, G. Raetsch, S. Stark, (2023).","ista":"Ficek J, Lehmann K-V, Locatello F, Raetsch G, Stark S. 2023. Methods of determining correspondences between biological properties of cells.","apa":"Ficek, J., Lehmann, K.-V., Locatello, F., Raetsch, G., &#38; Stark, S. (2023). Methods of determining correspondences between biological properties of cells."},"date_published":"2023-05-25T00:00:00Z","article_processing_charge":"No","OA_place":"repository","month":"05","applicant":["ETH Zürich"],"title":"Methods of determining correspondences between biological properties of cells","application_date":"2021-04-21","ddc":["540"],"status":"public","has_accepted_license":"1","date_created":"2024-02-08T15:52:21Z","type":"patent","day":"25"},{"day":"01","type":"conference","publication_status":"submitted","year":"2023","date_created":"2024-02-08T16:03:18Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","file":[{"relation":"main_file","content_type":"application/pdf","file_id":"14975","file_size":215629,"date_updated":"2024-02-08T16:03:08Z","file_name":"CLeaR23_roundtable_discussion.pdf","checksum":"105ff58e55de866ce76967f3a95e82f7","date_created":"2024-02-08T16:03:08Z","creator":"ptazenko","access_level":"open_access"}],"status":"public","has_accepted_license":"1","ddc":["000"],"file_date_updated":"2024-02-08T16:03:08Z","title":"Causality in the time of LLMs: Round table discussion results of CLeaR 2023","date_updated":"2025-08-05T11:19:37Z","month":"05","department":[{"_id":"FrLo"}],"language":[{"iso":"eng"}],"article_processing_charge":"No","abstract":[{"text":"The field of machine learning and AI has witnessed remarkable breakthroughs with the emergence of LLMs, which have also sparked a lively debate in the causal community. As researchers in this field, we are interested in exploring how LLMs relate to causality research, and how we can leverage the technology to advance it. In the second conference of Causal Learning and Reasoning (CLeaR), 2023, we held a round table discussion to gather and integrate the diverse perspectives of the CLeaR community on this topic.\r\nThere is a general consensus that LLMs are not yet capable of causal reasoning at the current\r\nstage but has a lot of potential with public available information by CLeaR 2023. Enhancing causal machine learning is vital not only for its own sake but also to help LLMs improve their performance, especially regarding trustworthiness. In this document, we present both the summary and the raw outcome of the round table discussion. We acknowledge that with the progress of both fields, the opportunities and impact may rapidly change. We will repeat the same exercise in CLeaR 2024 to document the evolution.","lang":"eng"}],"extern":"1","quality_controlled":"1","author":[{"full_name":"Zhang, Cheng","last_name":"Zhang","first_name":"Cheng"},{"first_name":"Dominik","last_name":"Janzing","full_name":"Janzing, Dominik"},{"first_name":"Mihaela ","last_name":"van der Schaar","full_name":"van der Schaar, Mihaela "},{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","last_name":"Locatello","first_name":"Francesco"},{"first_name":"Peter","last_name":"Spirtes","full_name":"Spirtes, Peter"},{"last_name":"Zhang","first_name":"Kun","full_name":"Zhang, Kun"},{"last_name":"Schölkopf","first_name":"Bernhard","full_name":"Schölkopf, Bernhard"},{"orcid":"0000-0002-7008-0216","full_name":"Uhler, Caroline","id":"49ADD78E-F248-11E8-B48F-1D18A9856A87","first_name":"Caroline","last_name":"Uhler"}],"publication":"2nd Conference on Causal Learning and Reasoning","date_published":"2023-05-01T00:00:00Z","oa":1,"citation":{"ama":"Zhang C, Janzing D, van der Schaar M, et al. Causality in the time of LLMs: Round table discussion results of CLeaR 2023. In: <i>2nd Conference on Causal Learning and Reasoning</i>.","ieee":"C. Zhang <i>et al.</i>, “Causality in the time of LLMs: Round table discussion results of CLeaR 2023,” in <i>2nd Conference on Causal Learning and Reasoning</i>, Tübingen, Germany.","chicago":"Zhang, Cheng, Dominik Janzing, Mihaela  van der Schaar, Francesco Locatello, Peter Spirtes, Kun Zhang, Bernhard Schölkopf, and Caroline Uhler. “Causality in the Time of LLMs: Round Table Discussion Results of CLeaR 2023.” In <i>2nd Conference on Causal Learning and Reasoning</i>, n.d.","mla":"Zhang, Cheng, et al. “Causality in the Time of LLMs: Round Table Discussion Results of CLeaR 2023.” <i>2nd Conference on Causal Learning and Reasoning</i>.","apa":"Zhang, C., Janzing, D., van der Schaar, M., Locatello, F., Spirtes, P., Zhang, K., … Uhler, C. (n.d.). Causality in the time of LLMs: Round table discussion results of CLeaR 2023. In <i>2nd Conference on Causal Learning and Reasoning</i>. Tübingen, Germany.","ista":"Zhang C, Janzing D, van der Schaar M, Locatello F, Spirtes P, Zhang K, Schölkopf B, Uhler C. Causality in the time of LLMs: Round table discussion results of CLeaR 2023. 2nd Conference on Causal Learning and Reasoning. CLeaR: Conference on Causal Learning and Reasoning.","short":"C. Zhang, D. Janzing, M. van der Schaar, F. Locatello, P. Spirtes, K. Zhang, B. Schölkopf, C. Uhler, in:, 2nd Conference on Causal Learning and Reasoning, n.d."},"conference":{"start_date":"2023-04-11","location":"Tübingen, Germany","end_date":"2023-04-14","name":"CLeaR: Conference on Causal Learning and Reasoning"},"oa_version":"Submitted Version","_id":"14974"},{"author":[{"full_name":"Liu, Zhengtao","first_name":"Zhengtao","last_name":"Liu"},{"first_name":"Tao","last_name":"Hong","full_name":"Hong, Tao"},{"full_name":"Xu, Liqing","last_name":"Xu","first_name":"Liqing"},{"full_name":"Wang, Sining","last_name":"Wang","first_name":"Sining"},{"first_name":"Xiang","last_name":"Gao","full_name":"Gao, Xiang"},{"last_name":"Chang","first_name":"Cheng","id":"9E331C2E-9F27-11E9-AE48-5033E6697425","full_name":"Chang, Cheng","orcid":"0000-0002-9515-4277"},{"first_name":"Xiangdong","last_name":"Ding","full_name":"Ding, Xiangdong"},{"last_name":"Xiao","first_name":"Yu","full_name":"Xiao, Yu"},{"full_name":"Zhao, Li‐Dong","last_name":"Zhao","first_name":"Li‐Dong"}],"abstract":[{"lang":"eng","text":"Lead sulfide (PbS) presents large potential in thermoelectric application due to its earth-abundant S element. However, its inferior average ZT (ZTave) value makes PbS less competitive with its analogs PbTe and PbSe. To promote its thermoelectric performance, this study implements strategies of continuous Se alloying and Cu interstitial doping to synergistically tune thermal and electrical transport properties in n-type PbS. First, the lattice parameter of 5.93 Å in PbS is linearly expanded to 6.03 Å in PbS0.5Se0.5 with increasing Se alloying content. This expanded lattice in Se-alloyed PbS not only intensifies phonon scattering but also facilitates the formation of Cu interstitials. Based on the PbS0.6Se0.4 content with the minimal lattice thermal conductivity, Cu interstitials are introduced to improve the electron density, thus boosting the peak power factor, from 3.88 μW cm−1 K−2 in PbS0.6Se0.4 to 20.58 μW cm−1 K−2 in PbS0.6Se0.4−1%Cu. Meanwhile, the lattice thermal conductivity in PbS0.6Se0.4−x%Cu (x = 0–2) is further suppressed due to the strong strain field caused by Cu interstitials. Finally, with the lowered thermal conductivity and high electrical transport properties, a peak ZT ~1.1 and ZTave ~0.82 can be achieved in PbS0.6Se0.4 − 1%Cu at 300–773K, which outperforms previously reported n-type PbS."}],"department":[{"_id":"MaIb"}],"_id":"14985","oa_version":"Published Version","article_type":"original","page":"161-170","oa":1,"file":[{"relation":"main_file","file_id":"15015","content_type":"application/pdf","date_updated":"2024-02-19T09:58:32Z","file_size":4675941,"file_name":"2023_InterdiscMaterials_Liu.pdf","checksum":"7b5e8210ef1434feb173022c6dbbee0c","date_created":"2024-02-19T09:58:32Z","success":1,"creator":"dernst","access_level":"open_access"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","volume":2,"year":"2023","publication_status":"published","date_updated":"2024-02-19T10:01:26Z","file_date_updated":"2024-02-19T09:58:32Z","publication":"Interdisciplinary Materials","article_processing_charge":"Yes","quality_controlled":"1","language":[{"iso":"eng"}],"publisher":"Wiley","month":"01","intvolume":"         2","tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"date_published":"2023-01-01T00:00:00Z","citation":{"chicago":"Liu, Zhengtao, Tao Hong, Liqing Xu, Sining Wang, Xiang Gao, Cheng Chang, Xiangdong Ding, Yu Xiao, and Li‐Dong Zhao. “Lattice Expansion Enables Interstitial Doping to Achieve a High Average ZT in N‐type PbS.” <i>Interdisciplinary Materials</i>. Wiley, 2023. <a href=\"https://doi.org/10.1002/idm2.12056\">https://doi.org/10.1002/idm2.12056</a>.","ieee":"Z. Liu <i>et al.</i>, “Lattice expansion enables interstitial doping to achieve a high average ZT in n‐type PbS,” <i>Interdisciplinary Materials</i>, vol. 2, no. 1. Wiley, pp. 161–170, 2023.","ama":"Liu Z, Hong T, Xu L, et al. Lattice expansion enables interstitial doping to achieve a high average ZT in n‐type PbS. <i>Interdisciplinary Materials</i>. 2023;2(1):161-170. doi:<a href=\"https://doi.org/10.1002/idm2.12056\">10.1002/idm2.12056</a>","mla":"Liu, Zhengtao, et al. “Lattice Expansion Enables Interstitial Doping to Achieve a High Average ZT in N‐type PbS.” <i>Interdisciplinary Materials</i>, vol. 2, no. 1, Wiley, 2023, pp. 161–70, doi:<a href=\"https://doi.org/10.1002/idm2.12056\">10.1002/idm2.12056</a>.","apa":"Liu, Z., Hong, T., Xu, L., Wang, S., Gao, X., Chang, C., … Zhao, L. (2023). Lattice expansion enables interstitial doping to achieve a high average ZT in n‐type PbS. <i>Interdisciplinary Materials</i>. Wiley. <a href=\"https://doi.org/10.1002/idm2.12056\">https://doi.org/10.1002/idm2.12056</a>","ista":"Liu Z, Hong T, Xu L, Wang S, Gao X, Chang C, Ding X, Xiao Y, Zhao L. 2023. Lattice expansion enables interstitial doping to achieve a high average ZT in n‐type PbS. Interdisciplinary Materials. 2(1), 161–170.","short":"Z. Liu, T. Hong, L. Xu, S. Wang, X. Gao, C. Chang, X. Ding, Y. Xiao, L. Zhao, Interdisciplinary Materials 2 (2023) 161–170."},"status":"public","has_accepted_license":"1","date_created":"2024-02-14T12:12:17Z","doi":"10.1002/idm2.12056","acknowledgement":"The authors would like to acknowledge the strong supportof microstructure observation from Center for HighPressure Science and Technology Advanced Research(HPSTAR). We acknowledge the financial support fromthe  National  Natural  Science  Foundation  of  China:52172236, the Fundamental Research Funds for theCentral Universities: xtr042021007, Top Young TalentsProgramme of Xi'an Jiaotong University and NationalScience Fund for Distinguished Young Scholars: 51925101.","day":"01","type":"journal_article","title":"Lattice expansion enables interstitial doping to achieve a high average ZT in n‐type PbS","issue":"1","ddc":["540"],"publication_identifier":{"eissn":["2767-441X"]}},{"main_file_link":[{"open_access":"1","url":"https://eprint.iacr.org/2023/081"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_created":"2024-02-14T14:20:40Z","doi":"10.14722/ndss.2023.24545","status":"public","publication_status":"published","type":"conference","day":"01","acknowledgement":"This work is supported by the Novi team at Meta and funded in part by IC3 industry partners and NSF grant 1943499.","year":"2023","title":"Parakeet: Practical key transparency for end-to-end eEncrypted messaging","date_updated":"2026-06-18T17:41:59Z","publication_identifier":{"isbn":["1891562835"]},"scopus_import":"1","ddc":["000"],"quality_controlled":"1","article_processing_charge":"No","abstract":[{"text":"Encryption alone is not enough for secure end-to end encrypted messaging: a server must also honestly serve public keys to users. Key transparency has been presented as an efficient\r\nsolution for detecting (and hence deterring) a server that attempts to dishonestly serve keys. Key transparency involves two major components: (1) a username to public key mapping, stored and cryptographically committed to by the server, and, (2) an outof-band consistency protocol for serving short commitments to users. In the setting of real-world deployments and supporting production scale, new challenges must be considered for both of these components. We enumerate these challenges and provide solutions to address them. In particular, we design and implement a memory-optimized and privacy-preserving verifiable data structure for committing to the username to public key store.\r\nTo make this implementation viable for production, we also integrate support for persistent and distributed storage. We also propose a future-facing solution, termed “compaction”, as\r\na mechanism for mitigating practical issues that arise from dealing with infinitely growing server data structures. Finally, we implement a consensusless solution that achieves the minimum requirements for a service that consistently distributes commitments for a transparency application, providing a much more efficient protocol for distributing small and consistent\r\ncommitments to users. This culminates in our production-grade implementation of a key transparency system (Parakeet) which we have open-sourced, along with a demonstration of feasibility through our benchmarks.","lang":"eng"}],"publication":"Proceedings of the 2023 Network and Distributed System Security Symposium","author":[{"full_name":"Malvai, Harjasleen","first_name":"Harjasleen","last_name":"Malvai"},{"full_name":"Kokoris Kogias, Eleftherios","orcid":"0000-0002-8827-3382","id":"f5983044-d7ef-11ea-ac6d-fd1430a26d30","first_name":"Eleftherios","last_name":"Kokoris Kogias"},{"first_name":"Alberto","last_name":"Sonnino","full_name":"Sonnino, Alberto"},{"full_name":"Ghosh, Esha","first_name":"Esha","last_name":"Ghosh"},{"full_name":"Oztürk, Ercan","last_name":"Oztürk","first_name":"Ercan"},{"first_name":"Kevin","last_name":"Lewi","full_name":"Lewi, Kevin"},{"full_name":"Lawlor, Sean","first_name":"Sean","last_name":"Lawlor"}],"month":"03","department":[{"_id":"ElKo"}],"publisher":"Internet Society","language":[{"iso":"eng"}],"oa_version":"Published Version","_id":"14989","citation":{"ama":"Malvai H, Kokoris Kogias E, Sonnino A, et al. Parakeet: Practical key transparency for end-to-end eEncrypted messaging. In: <i>Proceedings of the 2023 Network and Distributed System Security Symposium</i>. Internet Society; 2023. doi:<a href=\"https://doi.org/10.14722/ndss.2023.24545\">10.14722/ndss.2023.24545</a>","ieee":"H. Malvai <i>et al.</i>, “Parakeet: Practical key transparency for end-to-end eEncrypted messaging,” in <i>Proceedings of the 2023 Network and Distributed System Security Symposium</i>, San Diego, CA, United States, 2023.","chicago":"Malvai, Harjasleen, Eleftherios Kokoris Kogias, Alberto Sonnino, Esha Ghosh, Ercan Oztürk, Kevin Lewi, and Sean Lawlor. “Parakeet: Practical Key Transparency for End-to-End EEncrypted Messaging.” In <i>Proceedings of the 2023 Network and Distributed System Security Symposium</i>. Internet Society, 2023. <a href=\"https://doi.org/10.14722/ndss.2023.24545\">https://doi.org/10.14722/ndss.2023.24545</a>.","mla":"Malvai, Harjasleen, et al. “Parakeet: Practical Key Transparency for End-to-End EEncrypted Messaging.” <i>Proceedings of the 2023 Network and Distributed System Security Symposium</i>, Internet Society, 2023, doi:<a href=\"https://doi.org/10.14722/ndss.2023.24545\">10.14722/ndss.2023.24545</a>.","ista":"Malvai H, Kokoris Kogias E, Sonnino A, Ghosh E, Oztürk E, Lewi K, Lawlor S. 2023. Parakeet: Practical key transparency for end-to-end eEncrypted messaging. Proceedings of the 2023 Network and Distributed System Security Symposium. NDSS: Network and Distributed Systems Security.","apa":"Malvai, H., Kokoris Kogias, E., Sonnino, A., Ghosh, E., Oztürk, E., Lewi, K., &#38; Lawlor, S. (2023). Parakeet: Practical key transparency for end-to-end eEncrypted messaging. In <i>Proceedings of the 2023 Network and Distributed System Security Symposium</i>. San Diego, CA, United States: Internet Society. <a href=\"https://doi.org/10.14722/ndss.2023.24545\">https://doi.org/10.14722/ndss.2023.24545</a>","short":"H. Malvai, E. Kokoris Kogias, A. Sonnino, E. Ghosh, E. Oztürk, K. Lewi, S. Lawlor, in:, Proceedings of the 2023 Network and Distributed System Security Symposium, Internet Society, 2023."},"oa":1,"date_published":"2023-03-01T00:00:00Z","conference":{"start_date":"2023-02-27","location":"San Diego, CA, United States","end_date":"2023-03-03","name":"NDSS: Network and Distributed Systems Security"}},{"_id":"14990","tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"oa_version":"Published Version","oa":1,"citation":{"mla":"Meggendorfer, Tobias. <i>Artefact for: Correct Approximation of Stationary Distributions</i>. Zenodo, 2023, doi:<a href=\"https://doi.org/10.5281/ZENODO.7548214\">10.5281/ZENODO.7548214</a>.","ieee":"T. Meggendorfer, “Artefact for: Correct Approximation of Stationary Distributions.” Zenodo, 2023.","chicago":"Meggendorfer, Tobias. “Artefact for: Correct Approximation of Stationary Distributions.” Zenodo, 2023. <a href=\"https://doi.org/10.5281/ZENODO.7548214\">https://doi.org/10.5281/ZENODO.7548214</a>.","ama":"Meggendorfer T. Artefact for: Correct Approximation of Stationary Distributions. 2023. doi:<a href=\"https://doi.org/10.5281/ZENODO.7548214\">10.5281/ZENODO.7548214</a>","short":"T. Meggendorfer, (2023).","apa":"Meggendorfer, T. (2023). Artefact for: Correct Approximation of Stationary Distributions. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.7548214\">https://doi.org/10.5281/ZENODO.7548214</a>","ista":"Meggendorfer T. 2023. Artefact for: Correct Approximation of Stationary Distributions, Zenodo, <a href=\"https://doi.org/10.5281/ZENODO.7548214\">10.5281/ZENODO.7548214</a>."},"date_published":"2023-01-18T00:00:00Z","author":[{"id":"b21b0c15-30a2-11eb-80dc-f13ca25802e1","orcid":"0000-0002-1712-2165","full_name":"Meggendorfer, Tobias","last_name":"Meggendorfer","first_name":"Tobias"}],"article_processing_charge":"No","abstract":[{"lang":"eng","text":"The software artefact to evaluate the approximation of stationary distributions implementation."}],"publisher":"Zenodo","department":[{"_id":"KrCh"}],"month":"01","date_updated":"2025-09-09T12:28:12Z","title":"Artefact for: Correct Approximation of Stationary Distributions","corr_author":"1","ddc":["000"],"related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"13139"}]},"has_accepted_license":"1","status":"public","doi":"10.5281/ZENODO.7548214","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","main_file_link":[{"url":"https://doi.org/10.5281/zenodo.7548214","open_access":"1"}],"date_created":"2024-02-14T14:27:06Z","year":"2023","day":"18","type":"research_data_reference"},{"publisher":"Zenodo","department":[{"_id":"CaMu"}],"month":"06","author":[{"full_name":"Hwong, Yi-Ling","orcid":"0000-0001-9281-3479","id":"1217aa61-4dd1-11ec-9ac3-f2ba3f17ee22","first_name":"Yi-Ling","last_name":"Hwong"},{"last_name":"Colin","first_name":"Maxime","full_name":"Colin, Maxime"},{"id":"02eace56-97fc-11ee-b81a-f0939ca85a77","full_name":"Aglas, Philipp","last_name":"Aglas","first_name":"Philipp"},{"last_name":"Muller","first_name":"Caroline J","id":"f978ccb0-3f7f-11eb-b193-b0e2bd13182b","full_name":"Muller, Caroline J","orcid":"0000-0001-5836-5350"},{"full_name":"Sherwood, Steven C.","last_name":"Sherwood","first_name":"Steven C."}],"article_processing_charge":"No","abstract":[{"lang":"eng","text":"This repository contains the data, scripts, WRF codes and files required to reproduce the results of the manuscript \"Assessing Memory in Convection Schemes Using Idealized Tests\" submitted to the Journal of Advances in Modeling Earth Systems (JAMES)."}],"date_published":"2023-06-23T00:00:00Z","oa":1,"citation":{"ista":"Hwong Y-L, Colin M, Aglas P, Muller CJ, Sherwood SC. 2023. Data-assessing memory in convection schemes using idealized tests, Zenodo, <a href=\"https://doi.org/10.5281/ZENODO.7757041\">10.5281/ZENODO.7757041</a>.","apa":"Hwong, Y.-L., Colin, M., Aglas, P., Muller, C. J., &#38; Sherwood, S. C. (2023). Data-assessing memory in convection schemes using idealized tests. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.7757041\">https://doi.org/10.5281/ZENODO.7757041</a>","short":"Y.-L. Hwong, M. Colin, P. Aglas, C.J. Muller, S.C. Sherwood, (2023).","ieee":"Y.-L. Hwong, M. Colin, P. Aglas, C. J. Muller, and S. C. Sherwood, “Data-assessing memory in convection schemes using idealized tests.” Zenodo, 2023.","chicago":"Hwong, Yi-Ling, Maxime Colin, Philipp Aglas, Caroline J Muller, and Steven C. Sherwood. “Data-Assessing Memory in Convection Schemes Using Idealized Tests.” Zenodo, 2023. <a href=\"https://doi.org/10.5281/ZENODO.7757041\">https://doi.org/10.5281/ZENODO.7757041</a>.","ama":"Hwong Y-L, Colin M, Aglas P, Muller CJ, Sherwood SC. Data-assessing memory in convection schemes using idealized tests. 2023. doi:<a href=\"https://doi.org/10.5281/ZENODO.7757041\">10.5281/ZENODO.7757041</a>","mla":"Hwong, Yi-Ling, et al. <i>Data-Assessing Memory in Convection Schemes Using Idealized Tests</i>. Zenodo, 2023, doi:<a href=\"https://doi.org/10.5281/ZENODO.7757041\">10.5281/ZENODO.7757041</a>."},"project":[{"name":"IST-BRIDGE: International postdoctoral program","call_identifier":"H2020","grant_number":"101034413","_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c"}],"_id":"14991","ec_funded":1,"oa_version":"Published Version","tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"year":"2023","type":"research_data_reference","day":"23","related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"14654"}]},"status":"public","has_accepted_license":"1","doi":"10.5281/ZENODO.7757041","date_created":"2024-02-14T14:37:57Z","main_file_link":[{"open_access":"1","url":"https://doi.org/10.5281/zenodo.7757041"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","corr_author":"1","ddc":["550"],"date_updated":"2025-09-09T13:35:40Z","title":"Data-assessing memory in convection schemes using idealized tests"},{"edition":"1","page":"115-182","oa":1,"_id":"14992","oa_version":"Preprint","department":[{"_id":"RoSe"}],"author":[{"first_name":"Mathieu","last_name":"Lewin","full_name":"Lewin, Mathieu"},{"last_name":"Lieb","first_name":"Elliott H.","full_name":"Lieb, Elliott H."},{"first_name":"Robert","last_name":"Seiringer","full_name":"Seiringer, Robert","orcid":"0000-0002-6781-0521","id":"4AFD0470-F248-11E8-B48F-1D18A9856A87"}],"external_id":{"arxiv":["1912.10424"]},"abstract":[{"text":"In this chapter we first review the Levy–Lieb functional, which gives the lowest kinetic and interaction energy that can be reached with all possible quantum states having a given density. We discuss two possible convex generalizations of this functional, corresponding to using mixed canonical and grand-canonical states, respectively. We present some recent works about the local density approximation, in which the functionals get replaced by purely local functionals constructed using the uniform electron gas energy per unit volume. We then review the known upper and lower bounds on the Levy–Lieb functionals. We start with the kinetic energy alone, then turn to the classical interaction alone, before we are able to put everything together. A later section is devoted to the Hohenberg–Kohn theorem and the role of many-body unique continuation in its proof.","lang":"eng"}],"alternative_title":["Mathematics and Molecular Modeling"],"date_updated":"2024-02-20T08:33:06Z","series_title":"MAMOMO","year":"2023","publication_status":"published","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2023-07-19T00:00:00Z","citation":{"ieee":"M. Lewin, E. H. Lieb, and R. Seiringer, “Universal Functionals in Density Functional Theory,” in <i>Density Functional Theory</i>, 1st ed., E. Cances and G. Friesecke, Eds. Springer, 2023, pp. 115–182.","chicago":"Lewin, Mathieu, Elliott H. Lieb, and Robert Seiringer. “Universal Functionals in Density Functional Theory.” In <i>Density Functional Theory</i>, edited by Eric Cances and Gero Friesecke, 1st ed., 115–82. MAMOMO. Springer, 2023. <a href=\"https://doi.org/10.1007/978-3-031-22340-2_3\">https://doi.org/10.1007/978-3-031-22340-2_3</a>.","ama":"Lewin M, Lieb EH, Seiringer R. Universal Functionals in Density Functional Theory. In: Cances E, Friesecke G, eds. <i>Density Functional Theory</i>. 1st ed. MAMOMO. Springer; 2023:115-182. doi:<a href=\"https://doi.org/10.1007/978-3-031-22340-2_3\">10.1007/978-3-031-22340-2_3</a>","mla":"Lewin, Mathieu, et al. “Universal Functionals in Density Functional Theory.” <i>Density Functional Theory</i>, edited by Eric Cances and Gero Friesecke, 1st ed., Springer, 2023, pp. 115–82, doi:<a href=\"https://doi.org/10.1007/978-3-031-22340-2_3\">10.1007/978-3-031-22340-2_3</a>.","apa":"Lewin, M., Lieb, E. H., &#38; Seiringer, R. (2023). Universal Functionals in Density Functional Theory. In E. Cances &#38; G. Friesecke (Eds.), <i>Density Functional Theory</i> (1st ed., pp. 115–182). Springer. <a href=\"https://doi.org/10.1007/978-3-031-22340-2_3\">https://doi.org/10.1007/978-3-031-22340-2_3</a>","ista":"Lewin M, Lieb EH, Seiringer R. 2023.Universal Functionals in Density Functional Theory. In: Density Functional Theory. Mathematics and Molecular Modeling, , 115–182.","short":"M. Lewin, E.H. Lieb, R. Seiringer, in:, E. Cances, G. Friesecke (Eds.), Density Functional Theory, 1st ed., Springer, 2023, pp. 115–182."},"language":[{"iso":"eng"}],"publisher":"Springer","month":"07","publication":"Density Functional Theory","article_processing_charge":"No","quality_controlled":"1","editor":[{"last_name":"Cances","first_name":"Eric","full_name":"Cances, Eric"},{"first_name":"Gero","last_name":"Friesecke","full_name":"Friesecke, Gero"}],"publication_identifier":{"isbn":["9783031223396"],"eisbn":["9783031223402"],"issn":["3005-0286"]},"title":"Universal Functionals in Density Functional Theory","type":"book_chapter","day":"19","status":"public","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.1912.10424"}],"date_created":"2024-02-14T14:44:33Z","arxiv":1,"doi":"10.1007/978-3-031-22340-2_3"},{"citation":{"mla":"Currin, Christopher, et al. “A Framework for Grassroots Research Collaboration in Machine Learning and Global Health.” <i>1st Workshop on Machine Learning &#38; Global Health</i>, OpenReview, 2023.","chicago":"Currin, Christopher, Mercy Nyamewaa Asiedu , Chris Fourie, Benjamin Rosman, Houcemeddine Turki, Atnafu Lambebo Tonja, Jade Abbott, et al. “A Framework for Grassroots Research Collaboration in Machine Learning and Global Health.” In <i>1st Workshop on Machine Learning &#38; Global Health</i>. OpenReview, 2023.","ieee":"C. Currin <i>et al.</i>, “A framework for grassroots research collaboration in machine learning and global health,” in <i>1st Workshop on Machine Learning &#38; Global Health</i>, Kigali, Rwanda, 2023.","ama":"Currin C, Asiedu  MN, Fourie C, et al. A framework for grassroots research collaboration in machine learning and global health. In: <i>1st Workshop on Machine Learning &#38; Global Health</i>. OpenReview; 2023.","short":"C. Currin, M.N. Asiedu , C. Fourie, B. Rosman, H. Turki, A. Lambebo Tonja, J. Abbott, M. Ajala, S.A. Adedayo, C.C. Emezue, D. Machangara, in:, 1st Workshop on Machine Learning &#38; Global Health, OpenReview, 2023.","ista":"Currin C, Asiedu  MN, Fourie C, Rosman B, Turki H, Lambebo Tonja A, Abbott J, Ajala M, Adedayo SA, Emezue CC, Machangara D. 2023. A framework for grassroots research collaboration in machine learning and global health. 1st Workshop on Machine Learning &#38; Global Health. ICLR: International Conference on Learning Representations.","apa":"Currin, C., Asiedu , M. N., Fourie, C., Rosman, B., Turki, H., Lambebo Tonja, A., … Machangara, D. (2023). A framework for grassroots research collaboration in machine learning and global health. In <i>1st Workshop on Machine Learning &#38; Global Health</i>. Kigali, Rwanda: OpenReview."},"oa":1,"date_published":"2023-03-02T00:00:00Z","conference":{"end_date":"2023-05-05","name":"ICLR: International Conference on Learning Representations","location":"Kigali, Rwanda","start_date":"2023-05-05"},"oa_version":"Published Version","_id":"14993","department":[{"_id":"TiVo"}],"month":"03","publisher":"OpenReview","language":[{"iso":"eng"}],"quality_controlled":"1","abstract":[{"lang":"eng","text":"Traditional top-down approaches for global health have historically failed to achieve social progress (Hoffman et al., 2015; Hoffman & Røttingen, 2015). Recently, however, a more holistic, multi-level approach termed One Health (OH) (Osterhaus et al., 2020) is being adopted. Several sets of challenges have been identified for the implementation of OH (dos S. Ribeiro et al., 2019), including policy and funding, education and training, and multi-actor, multi-domain, and multi-level collaborations. These exist despite the increasing accessibility to\r\nknowledge and digital collaborative research tools through the internet. To address some of these challenges, we propose a general framework for grassroots community-based means of participatory research. Additionally, we present a specific roadmap to create a Machine Learning for Global Health community in Africa. The proposed framework aims to enable any small group of individuals with scarce resources to build and sustain an online community within approximately two years. We provide a discussion on the potential impact of the proposed framework for global health research collaborations."}],"article_processing_charge":"No","publication":"1st Workshop on Machine Learning & Global Health","author":[{"first_name":"Christopher","last_name":"Currin","full_name":"Currin, Christopher","orcid":"0000-0002-4809-5059","id":"e8321fc5-3091-11eb-8a53-83f309a11ac9"},{"full_name":"Asiedu , Mercy Nyamewaa","last_name":"Asiedu ","first_name":"Mercy Nyamewaa"},{"full_name":"Fourie, Chris","first_name":"Chris","last_name":"Fourie"},{"last_name":"Rosman","first_name":"Benjamin","full_name":"Rosman, Benjamin"},{"first_name":"Houcemeddine","last_name":"Turki","full_name":"Turki, Houcemeddine"},{"full_name":"Lambebo Tonja, Atnafu","first_name":"Atnafu","last_name":"Lambebo Tonja"},{"full_name":"Abbott, Jade","first_name":"Jade","last_name":"Abbott"},{"full_name":"Ajala, Marvellous","first_name":"Marvellous","last_name":"Ajala"},{"full_name":"Adedayo, Sadiq Adewale","first_name":"Sadiq Adewale","last_name":"Adedayo"},{"first_name":"Chris Chinenye","last_name":"Emezue","full_name":"Emezue, Chris Chinenye"},{"full_name":"Machangara, Daphne","last_name":"Machangara","first_name":"Daphne"}],"ddc":["000"],"title":"A framework for grassroots research collaboration in machine learning and global health","date_updated":"2026-06-18T17:42:25Z","publication_status":"published","day":"02","type":"conference","acknowledgement":"Houcemeddine Turki’s contributions to this final output have been funded through the Adapting\r\nWikidata to support clinical practice using Data Science, Semantic Web and Machine Learning\r\nproject, which is part of the Wikimedia Research Fund maintained by the Wikimedia Foundation in San Francisco, California, United States of America.","year":"2023","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_created":"2024-02-14T15:11:48Z","main_file_link":[{"open_access":"1","url":"https://openreview.net/forum?id=jHY_G91R880"}],"status":"public"},{"corr_author":"1","ddc":["000"],"title":"A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties","date_updated":"2025-09-09T14:16:48Z","day":"28","type":"research_data_reference","year":"2023","main_file_link":[{"open_access":"1","url":"https://doi.org/10.5281/zenodo.7877790"}],"date_created":"2024-02-14T15:13:00Z","doi":"10.5281/ZENODO.7877790","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","status":"public","related_material":{"record":[{"id":"14758","status":"public","relation":"used_in_publication"}]},"has_accepted_license":"1","date_published":"2023-04-28T00:00:00Z","citation":{"ista":"Majumdar R, Mallik K, Rychlicki M, Schmuck A-K, Soudjani S. 2023. A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties, Zenodo, <a href=\"https://doi.org/10.5281/ZENODO.7877790\">10.5281/ZENODO.7877790</a>.","apa":"Majumdar, R., Mallik, K., Rychlicki, M., Schmuck, A.-K., &#38; Soudjani, S. (2023). A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.7877790\">https://doi.org/10.5281/ZENODO.7877790</a>","short":"R. Majumdar, K. Mallik, M. Rychlicki, A.-K. Schmuck, S. Soudjani, (2023).","chicago":"Majumdar, Rupak, Kaushik Mallik, Mateusz Rychlicki, Anne-Kathrin Schmuck, and Sadegh Soudjani. “A Flexible Toolchain for Symbolic Rabin Games under Fair and Stochastic Uncertainties.” Zenodo, 2023. <a href=\"https://doi.org/10.5281/ZENODO.7877790\">https://doi.org/10.5281/ZENODO.7877790</a>.","ieee":"R. Majumdar, K. Mallik, M. Rychlicki, A.-K. Schmuck, and S. Soudjani, “A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties.” Zenodo, 2023.","ama":"Majumdar R, Mallik K, Rychlicki M, Schmuck A-K, Soudjani S. A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties. 2023. doi:<a href=\"https://doi.org/10.5281/ZENODO.7877790\">10.5281/ZENODO.7877790</a>","mla":"Majumdar, Rupak, et al. <i>A Flexible Toolchain for Symbolic Rabin Games under Fair and Stochastic Uncertainties</i>. Zenodo, 2023, doi:<a href=\"https://doi.org/10.5281/ZENODO.7877790\">10.5281/ZENODO.7877790</a>."},"oa":1,"oa_version":"Published Version","tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"_id":"14994","department":[{"_id":"ToHe"}],"month":"04","publisher":"Zenodo","article_processing_charge":"No","abstract":[{"text":"This resource contains the artifacts for reproducing the experimental results presented in the paper titled \"A Flexible Toolchain for Symbolic Rabin Games under Fair and Stochastic Uncertainties\" that has been submitted in CAV 2023.","lang":"eng"}],"author":[{"last_name":"Majumdar","first_name":"Rupak","full_name":"Majumdar, Rupak"},{"first_name":"Kaushik","last_name":"Mallik","full_name":"Mallik, Kaushik","orcid":"0000-0001-9864-7475","id":"0834ff3c-6d72-11ec-94e0-b5b0a4fb8598"},{"full_name":"Rychlicki, Mateusz","first_name":"Mateusz","last_name":"Rychlicki"},{"full_name":"Schmuck, Anne-Kathrin","first_name":"Anne-Kathrin","last_name":"Schmuck"},{"full_name":"Soudjani, Sadegh","last_name":"Soudjani","first_name":"Sadegh"}]},{"ddc":["000"],"date_updated":"2025-09-09T12:51:51Z","title":"Lincheck: A practical framework for testing concurrent data structures on JVM","year":"2023","day":"28","type":"research_data_reference","related_material":{"record":[{"status":"public","relation":"used_in_publication","id":"14260"}]},"status":"public","main_file_link":[{"open_access":"1","url":"https://doi.org/10.5281/zenodo.7877757"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_created":"2024-02-14T15:14:13Z","doi":"10.5281/ZENODO.7877757","oa":1,"citation":{"ieee":"N. Koval, A. Fedorov, M. Sokolova, D. Tsitelov, and D.-A. Alistarh, “Lincheck: A practical framework for testing concurrent data structures on JVM.” Zenodo, 2023.","chicago":"Koval, Nikita, Alexander Fedorov, Maria Sokolova, Dmitry Tsitelov, and Dan-Adrian Alistarh. “Lincheck: A Practical Framework for Testing Concurrent Data Structures on JVM.” Zenodo, 2023. <a href=\"https://doi.org/10.5281/ZENODO.7877757\">https://doi.org/10.5281/ZENODO.7877757</a>.","ama":"Koval N, Fedorov A, Sokolova M, Tsitelov D, Alistarh D-A. Lincheck: A practical framework for testing concurrent data structures on JVM. 2023. doi:<a href=\"https://doi.org/10.5281/ZENODO.7877757\">10.5281/ZENODO.7877757</a>","mla":"Koval, Nikita, et al. <i>Lincheck: A Practical Framework for Testing Concurrent Data Structures on JVM</i>. Zenodo, 2023, doi:<a href=\"https://doi.org/10.5281/ZENODO.7877757\">10.5281/ZENODO.7877757</a>.","ista":"Koval N, Fedorov A, Sokolova M, Tsitelov D, Alistarh D-A. 2023. Lincheck: A practical framework for testing concurrent data structures on JVM, Zenodo, <a href=\"https://doi.org/10.5281/ZENODO.7877757\">10.5281/ZENODO.7877757</a>.","apa":"Koval, N., Fedorov, A., Sokolova, M., Tsitelov, D., &#38; Alistarh, D.-A. (2023). Lincheck: A practical framework for testing concurrent data structures on JVM. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.7877757\">https://doi.org/10.5281/ZENODO.7877757</a>","short":"N. Koval, A. Fedorov, M. Sokolova, D. Tsitelov, D.-A. Alistarh, (2023)."},"date_published":"2023-04-28T00:00:00Z","_id":"14995","oa_version":"Published Version","publisher":"Zenodo","month":"04","department":[{"_id":"DaAl"}],"author":[{"id":"2F4DB10C-F248-11E8-B48F-1D18A9856A87","full_name":"Koval, Nikita","last_name":"Koval","first_name":"Nikita"},{"last_name":"Fedorov","first_name":"Alexander","id":"2e711909-896a-11ed-bdf8-eb0f5a2984c6","full_name":"Fedorov, Alexander"},{"last_name":"Sokolova","first_name":"Maria","full_name":"Sokolova, Maria"},{"first_name":"Dmitry","last_name":"Tsitelov","full_name":"Tsitelov, Dmitry"},{"last_name":"Alistarh","first_name":"Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-3650-940X","full_name":"Alistarh, Dan-Adrian"}],"abstract":[{"lang":"eng","text":"Lincheck is a new practical and user-friendly framework for testing concurrent data structures on the Java Virtual Machine (JVM). It provides a simple and declarative way to write concurrent tests. Instead of describing how to perform the test, users specify what to test by declaring all the operations to examine; the framework automatically handles the rest. As a result, tests written with Lincheck are concise and easy to understand. \r\nThe artifact presents a collection of Lincheck tests that discover new bugs in popular libraries and implementations from the concurrency literature -- they are listed in Table 1, Section 3. To evaluate the performance of Lincheck analysis, the collection of tests also includes those which check correct data structures and, thus, always succeed. Similarly to Table 2, Section 3, the experiments demonstrate the reasonable time to perform a test. Finally, Lincheck provides user-friendly output with an easy-to-follow trace to reproduce a detected error, significantly simplifying further investigation."}],"article_processing_charge":"No"},{"oa":1,"_id":"15023","ec_funded":1,"project":[{"name":"Formal Methods for Stochastic Models: Algorithms and Applications","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","grant_number":"863818","call_identifier":"H2020"},{"_id":"62781420-2b32-11ec-9570-8d9b63373d4d","grant_number":"101020093","call_identifier":"H2020","name":"Vigilant Algorithmic Monitoring of Software"}],"oa_version":"Published Version","department":[{"_id":"ToHe"},{"_id":"KrCh"}],"external_id":{"arxiv":["2312.01456"]},"author":[{"orcid":"0000-0002-4681-1699","full_name":"Zikelic, Dorde","id":"294AA7A6-F248-11E8-B48F-1D18A9856A87","first_name":"Dorde","last_name":"Zikelic"},{"first_name":"Mathias","last_name":"Lechner","full_name":"Lechner, Mathias","id":"3DC22916-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Abhinav","last_name":"Verma","full_name":"Verma, Abhinav","id":"a235593c-d7fa-11eb-a0c5-b22ca3c66ee6"},{"id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4561-241X","full_name":"Chatterjee, Krishnendu","last_name":"Chatterjee","first_name":"Krishnendu"},{"id":"40876CD8-F248-11E8-B48F-1D18A9856A87","full_name":"Henzinger, Thomas A","orcid":"0000-0002-2985-7724","last_name":"Henzinger","first_name":"Thomas A"}],"abstract":[{"text":"Reinforcement learning has shown promising results in learning neural network policies for complicated control tasks. However, the lack of formal guarantees about the behavior of such policies remains an impediment to their deployment. We propose a novel method for learning a composition of neural network policies in stochastic environments, along with a formal certificate which guarantees that a specification over the policy's behavior is satisfied with the desired probability. Unlike prior work on verifiable RL, our approach leverages the compositional nature of logical specifications provided in SpectRL, to learn over graphs of probabilistic reach-avoid specifications. The formal guarantees are provided by learning neural network policies together with reach-avoid supermartingales (RASM) for the graph’s sub-tasks and then composing them into a global policy. We also derive a tighter lower bound compared to previous work on the probability of reach-avoidance implied by a RASM, which is required to find a compositional policy with an acceptable probabilistic threshold for complex tasks with multiple edge policies. We implement a prototype of our approach and evaluate it on a Stochastic Nine Rooms environment.","lang":"eng"}],"alternative_title":["NeurIPS"],"file_date_updated":"2024-07-22T11:45:17Z","date_updated":"2025-04-14T07:52:48Z","year":"2023","publication_status":"published","file":[{"access_level":"open_access","creator":"dernst","success":1,"date_created":"2024-07-22T11:45:17Z","checksum":"739c6d72506b778302d4e708723bf12c","file_name":"2023_NeurIPS_Zikelic.pdf","date_updated":"2024-07-22T11:45:17Z","file_size":562008,"file_id":"17309","content_type":"application/pdf","relation":"main_file"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","conference":{"end_date":"2023-12-16","name":"NeurIPS: Neural Information Processing Systems","start_date":"2023-12-10","location":"New Orleans, LO, United States"},"citation":{"mla":"Zikelic, Dorde, et al. “Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees.” <i>37th Conference on Neural Information Processing Systems</i>, 2023.","ama":"Zikelic D, Lechner M, Verma A, Chatterjee K, Henzinger TA. Compositional policy learning in stochastic control systems with formal guarantees. In: <i>37th Conference on Neural Information Processing Systems</i>. ; 2023.","chicago":"Zikelic, Dorde, Mathias Lechner, Abhinav Verma, Krishnendu Chatterjee, and Thomas A Henzinger. “Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees.” In <i>37th Conference on Neural Information Processing Systems</i>, 2023.","ieee":"D. Zikelic, M. Lechner, A. Verma, K. Chatterjee, and T. A. Henzinger, “Compositional policy learning in stochastic control systems with formal guarantees,” in <i>37th Conference on Neural Information Processing Systems</i>, New Orleans, LO, United States, 2023.","short":"D. Zikelic, M. Lechner, A. Verma, K. Chatterjee, T.A. Henzinger, in:, 37th Conference on Neural Information Processing Systems, 2023.","apa":"Zikelic, D., Lechner, M., Verma, A., Chatterjee, K., &#38; Henzinger, T. A. (2023). Compositional policy learning in stochastic control systems with formal guarantees. In <i>37th Conference on Neural Information Processing Systems</i>. New Orleans, LO, United States.","ista":"Zikelic D, Lechner M, Verma A, Chatterjee K, Henzinger TA. 2023. Compositional policy learning in stochastic control systems with formal guarantees. 37th Conference on Neural Information Processing Systems. 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Figshare, 2023.","ieee":"S. Curk, “aggregation_data.” Figshare, 2023.","chicago":"Curk, Samo. “Aggregation_data.” Figshare, 2023.","ama":"Curk S. aggregation_data. 2023.","short":"S. Curk, (2023).","apa":"Curk, S. (2023). aggregation_data. Figshare.","ista":"Curk S. 2023. aggregation_data, Figshare."},"date_published":"2023-12-13T00:00:00Z","article_processing_charge":"No","abstract":[{"text":"This data repository underpins the paper, published in PNAS (doi pending) and bioarxiv (doi: https://doi.org/10.1101/2023.07.05.547777).","lang":"eng"}],"author":[{"first_name":"Samo","last_name":"Curk","full_name":"Curk, Samo","orcid":"0000-0001-6160-9766","id":"031eff0d-d481-11ee-8508-cd12a7a86e5b"}],"month":"12","department":[{"_id":"AnSa"}],"license":"https://creativecommons.org/publicdomain/zero/1.0/","OA_place":"publisher","publisher":"Figshare"},{"date_published":"2023-07-28T00:00:00Z","oa":1,"citation":{"apa":"Chalupa, M., &#38; Henzinger, T. A. (2023). Monitoring hyperproperties with prefix transducers. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.8191723\">https://doi.org/10.5281/ZENODO.8191723</a>","ista":"Chalupa M, Henzinger TA. 2023. Monitoring hyperproperties with prefix transducers, Zenodo, <a href=\"https://doi.org/10.5281/ZENODO.8191723\">10.5281/ZENODO.8191723</a>.","short":"M. Chalupa, T.A. Henzinger, (2023).","ama":"Chalupa M, Henzinger TA. Monitoring hyperproperties with prefix transducers. 2023. doi:<a href=\"https://doi.org/10.5281/ZENODO.8191723\">10.5281/ZENODO.8191723</a>","chicago":"Chalupa, Marek, and Thomas A Henzinger. “Monitoring Hyperproperties with Prefix Transducers.” Zenodo, 2023. <a href=\"https://doi.org/10.5281/ZENODO.8191723\">https://doi.org/10.5281/ZENODO.8191723</a>.","ieee":"M. Chalupa and T. A. Henzinger, “Monitoring hyperproperties with prefix transducers.” Zenodo, 2023.","mla":"Chalupa, Marek, and Thomas A. Henzinger. <i>Monitoring Hyperproperties with Prefix Transducers</i>. Zenodo, 2023, doi:<a href=\"https://doi.org/10.5281/ZENODO.8191723\">10.5281/ZENODO.8191723</a>."},"project":[{"grant_number":"101020093","_id":"62781420-2b32-11ec-9570-8d9b63373d4d","call_identifier":"H2020","name":"Vigilant Algorithmic Monitoring of Software"}],"_id":"15035","ec_funded":1,"tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"oa_version":"Published Version","publisher":"Zenodo","department":[{"_id":"ToHe"}],"month":"07","author":[{"full_name":"Chalupa, Marek","id":"87e34708-d6c6-11ec-9f5b-9391e7be2463","first_name":"Marek","last_name":"Chalupa"},{"full_name":"Henzinger, Thomas A","orcid":"0000-0002-2985-7724","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","first_name":"Thomas A","last_name":"Henzinger"}],"article_processing_charge":"No","abstract":[{"lang":"eng","text":"This artifact aims to reproduce experiments from the paper Monitoring Hyperproperties With Prefix Transducers accepted at RV'23, and give further pointers to implementation of prefix transducers.\r\nIt has two parts: a pre-compiled docker image and sources that one can use to compile (locally or in docker) the software and run the experiments."}],"corr_author":"1","ddc":["000"],"date_updated":"2025-04-14T09:42:55Z","title":"Monitoring hyperproperties with prefix transducers","year":"2023","type":"research_data_reference","day":"28","status":"public","related_material":{"record":[{"status":"public","relation":"used_in_publication","id":"14076"}]},"has_accepted_license":"1","main_file_link":[{"url":"https://doi.org/10.5281/zenodo.8191722","open_access":"1"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_created":"2024-02-28T07:34:34Z","doi":"10.5281/ZENODO.8191723"},{"corr_author":"1","title":"1-Lipschitz neural networks are more expressive with N-activations","date_updated":"2026-04-07T11:49:51Z","day":"10","type":"preprint","publication_status":"draft","year":"2023","date_created":"2024-02-28T17:59:32Z","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2311.06103","open_access":"1"}],"doi":"10.48550/ARXIV.2311.06103","arxiv":1,"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","status":"public","related_material":{"record":[{"id":"19759","relation":"dissertation_contains","status":"public"}]},"date_published":"2023-11-10T00:00:00Z","citation":{"ista":"Prach B, Lampert C. 1-Lipschitz neural networks are more expressive with N-activations. arXiv, 2311.06103.","apa":"Prach, B., &#38; Lampert, C. (n.d.). 1-Lipschitz neural networks are more expressive with N-activations. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/ARXIV.2311.06103\">https://doi.org/10.48550/ARXIV.2311.06103</a>","short":"B. Prach, C. Lampert, ArXiv (n.d.).","chicago":"Prach, Bernd, and Christoph Lampert. “1-Lipschitz Neural Networks Are More Expressive with N-Activations.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/ARXIV.2311.06103\">https://doi.org/10.48550/ARXIV.2311.06103</a>.","ieee":"B. Prach and C. Lampert, “1-Lipschitz neural networks are more expressive with N-activations,” <i>arXiv</i>. .","ama":"Prach B, Lampert C. 1-Lipschitz neural networks are more expressive with N-activations. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/ARXIV.2311.06103\">10.48550/ARXIV.2311.06103</a>","mla":"Prach, Bernd, and Christoph Lampert. “1-Lipschitz Neural Networks Are More Expressive with N-Activations.” <i>ArXiv</i>, 2311.06103, doi:<a href=\"https://doi.org/10.48550/ARXIV.2311.06103\">10.48550/ARXIV.2311.06103</a>."},"oa":1,"oa_version":"Preprint","tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"article_number":"2311.06103","_id":"15039","month":"11","department":[{"_id":"GradSch"},{"_id":"ChLa"}],"language":[{"iso":"eng"}],"OA_place":"repository","abstract":[{"lang":"eng","text":"A crucial property for achieving secure, trustworthy and interpretable deep learning systems is their robustness: small changes to a system's inputs should not result in large changes to its outputs. Mathematically, this means one strives for networks with a small Lipschitz constant. Several recent works have focused on how to construct such Lipschitz networks, typically by imposing constraints on the weight matrices. In this work, we study an orthogonal aspect, namely the role of the activation function. We show that commonly used activation functions, such as MaxMin, as well as all piece-wise linear ones with two segments unnecessarily restrict the class of representable functions, even in the simplest one-dimensional setting. We furthermore introduce the new N-activation function that is provably more expressive than currently popular activation functions. We provide code at this https URL."}],"article_processing_charge":"No","author":[{"id":"2D561D42-C427-11E9-89B4-9C1AE6697425","full_name":"Prach, Bernd","last_name":"Prach","first_name":"Bernd"},{"orcid":"0000-0001-8622-7887","full_name":"Lampert, Christoph","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","first_name":"Christoph","last_name":"Lampert"}],"external_id":{"arxiv":["2311.06103"]},"publication":"arXiv"},{"issue":"6676","title":"An observed population of intermediate-mass helium stars that have been stripped in binaries","scopus_import":"1","publication_identifier":{"issn":["0036-8075"],"eissn":["1095-9203"]},"doi":"10.1126/science.ade4970","date_created":"2024-03-05T09:40:28Z","arxiv":1,"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2307.00061"}],"status":"public","day":"14","type":"journal_article","intvolume":"       382","date_published":"2023-12-14T00:00:00Z","citation":{"short":"M.R. Drout, Y.L.L. Götberg, B.A. Ludwig, J.H. Groh, S.E. de Mink, A.J.G. O’Grady, N. Smith, Science 382 (2023) 1287–1291.","apa":"Drout, M. R., Götberg, Y. L. L., Ludwig, B. A., Groh, J. H., de Mink, S. E., O’Grady, A. J. G., &#38; Smith, N. (2023). An observed population of intermediate-mass helium stars that have been stripped in binaries. <i>Science</i>. American Association for the Advancement of Science. <a href=\"https://doi.org/10.1126/science.ade4970\">https://doi.org/10.1126/science.ade4970</a>","ista":"Drout MR, Götberg YLL, Ludwig BA, Groh JH, de Mink SE, O’Grady AJG, Smith N. 2023. An observed population of intermediate-mass helium stars that have been stripped in binaries. Science. 382(6676), 1287–1291.","mla":"Drout, M. R., et al. “An Observed Population of Intermediate-Mass Helium Stars That Have Been Stripped in Binaries.” <i>Science</i>, vol. 382, no. 6676, American Association for the Advancement of Science, 2023, pp. 1287–91, doi:<a href=\"https://doi.org/10.1126/science.ade4970\">10.1126/science.ade4970</a>.","ama":"Drout MR, Götberg YLL, Ludwig BA, et al. An observed population of intermediate-mass helium stars that have been stripped in binaries. <i>Science</i>. 2023;382(6676):1287-1291. doi:<a href=\"https://doi.org/10.1126/science.ade4970\">10.1126/science.ade4970</a>","chicago":"Drout, M. R., Ylva Louise Linsdotter Götberg, B. A. Ludwig, J. H. Groh, S. E. de Mink, A. J. G. O’Grady, and N. Smith. “An Observed Population of Intermediate-Mass Helium Stars That Have Been Stripped in Binaries.” <i>Science</i>. American Association for the Advancement of Science, 2023. <a href=\"https://doi.org/10.1126/science.ade4970\">https://doi.org/10.1126/science.ade4970</a>.","ieee":"M. R. Drout <i>et al.</i>, “An observed population of intermediate-mass helium stars that have been stripped in binaries,” <i>Science</i>, vol. 382, no. 6676. American Association for the Advancement of Science, pp. 1287–1291, 2023."},"article_processing_charge":"No","quality_controlled":"1","publication":"Science","pmid":1,"month":"12","language":[{"iso":"eng"}],"publisher":"American Association for the Advancement of Science","keyword":["Stellar Astrophysics"],"date_updated":"2024-10-14T12:32:01Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","related_material":{"link":[{"url":"https://ista.ac.at/en/news/reaching-for-the-invisible-stars/","relation":"press_release","description":"News on ISTA Website"}]},"publication_status":"published","year":"2023","volume":382,"oa_version":"None","_id":"15085","oa":1,"article_type":"original","page":"1287-1291","extern":"1","abstract":[{"lang":"eng","text":"The hydrogen-rich outer layers of massive stars can be removed by interactions with a binary companion. Theoretical models predict that this stripping produces a population of hot helium stars of ~2 to 8 solar masses (M☉), however, only one such system has been identified thus far. We used ultraviolet photometry to identify potential stripped helium stars then investigated 25 of them using optical spectroscopy. We identified stars with high temperatures (~60,000 to 100,000 kelvin), high surface gravities, and hydrogen-depleted surfaces; 16 stars also showed binary motion. These properties match expectations for stars with initial masses of 8 to 25 M☉ that were stripped by binary interaction. Their masses fall in the gap between subdwarf helium stars and Wolf-Rayet stars. We propose that these stars could be progenitors of stripped-envelope supernovae."}],"author":[{"last_name":"Drout","first_name":"M. R.","full_name":"Drout, M. R."},{"first_name":"Ylva Louise Linsdotter","last_name":"Götberg","full_name":"Götberg, Ylva Louise Linsdotter","orcid":"0000-0002-6960-6911","id":"d0648d0c-0f64-11ee-a2e0-dd0faa2e4f7d"},{"full_name":"Ludwig, B. A.","first_name":"B. A.","last_name":"Ludwig"},{"full_name":"Groh, J. H.","last_name":"Groh","first_name":"J. H."},{"full_name":"de Mink, S. E.","first_name":"S. E.","last_name":"de Mink"},{"last_name":"O’Grady","first_name":"A. J. G.","full_name":"O’Grady, A. J. G."},{"full_name":"Smith, N.","first_name":"N.","last_name":"Smith"}],"external_id":{"pmid":["38096420"],"arxiv":["2307.00061"]}},{"status":"public","date_created":"2024-03-20T10:40:56Z","doi":"10.1016/j.molcel.2023.01.024","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1016/j.molcel.2023.01.024"}],"day":"02","type":"journal_article","issue":"5","title":"Structural snapshots of R-loop formation by a type I-C CRISPR Cascade","scopus_import":"1","publication_identifier":{"issn":["1097-2765"]},"publication":"Molecular Cell","article_processing_charge":"Yes (in subscription journal)","quality_controlled":"1","language":[{"iso":"eng"}],"publisher":"Elsevier","pmid":1,"month":"03","intvolume":"        83","date_published":"2023-03-02T00:00:00Z","citation":{"short":"R.E. O’Brien, J.P.K. Bravo, D. Ramos, G.N. Hibshman, J.T. Wright, D.W. Taylor, Molecular Cell 83 (2023) 746–758.e5.","ista":"O’Brien RE, Bravo JPK, Ramos D, Hibshman GN, Wright JT, Taylor DW. 2023. Structural snapshots of R-loop formation by a type I-C CRISPR Cascade. Molecular Cell. 83(5), 746–758.e5.","apa":"O’Brien, R. E., Bravo, J. P. K., Ramos, D., Hibshman, G. N., Wright, J. T., &#38; Taylor, D. W. (2023). Structural snapshots of R-loop formation by a type I-C CRISPR Cascade. <i>Molecular Cell</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.molcel.2023.01.024\">https://doi.org/10.1016/j.molcel.2023.01.024</a>","mla":"O’Brien, Roisin E., et al. “Structural Snapshots of R-Loop Formation by a Type I-C CRISPR Cascade.” <i>Molecular Cell</i>, vol. 83, no. 5, Elsevier, 2023, p. 746–758.e5, doi:<a href=\"https://doi.org/10.1016/j.molcel.2023.01.024\">10.1016/j.molcel.2023.01.024</a>.","ama":"O’Brien RE, Bravo JPK, Ramos D, Hibshman GN, Wright JT, Taylor DW. Structural snapshots of R-loop formation by a type I-C CRISPR Cascade. <i>Molecular Cell</i>. 2023;83(5):746-758.e5. doi:<a href=\"https://doi.org/10.1016/j.molcel.2023.01.024\">10.1016/j.molcel.2023.01.024</a>","ieee":"R. E. O’Brien, J. P. K. Bravo, D. Ramos, G. N. Hibshman, J. T. Wright, and D. W. Taylor, “Structural snapshots of R-loop formation by a type I-C CRISPR Cascade,” <i>Molecular Cell</i>, vol. 83, no. 5. Elsevier, p. 746–758.e5, 2023.","chicago":"O’Brien, Roisin E., Jack Peter Kelly Bravo, Delisa Ramos, Grace N. Hibshman, Jacquelyn T. Wright, and David W. Taylor. “Structural Snapshots of R-Loop Formation by a Type I-C CRISPR Cascade.” <i>Molecular Cell</i>. Elsevier, 2023. <a href=\"https://doi.org/10.1016/j.molcel.2023.01.024\">https://doi.org/10.1016/j.molcel.2023.01.024</a>."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2023","volume":83,"publication_status":"published","date_updated":"2024-06-04T06:33:54Z","keyword":["Cell Biology","Molecular Biology"],"author":[{"first_name":"Roisin E.","last_name":"O’Brien","full_name":"O’Brien, Roisin E."},{"id":"96aecfa5-8931-11ee-af30-aa6a5d6eee0e","orcid":"0000-0003-0456-0753","full_name":"Bravo, Jack Peter Kelly","last_name":"Bravo","first_name":"Jack Peter Kelly"},{"first_name":"Delisa","last_name":"Ramos","full_name":"Ramos, Delisa"},{"full_name":"Hibshman, Grace N.","first_name":"Grace N.","last_name":"Hibshman"},{"full_name":"Wright, Jacquelyn T.","first_name":"Jacquelyn T.","last_name":"Wright"},{"full_name":"Taylor, David W.","first_name":"David W.","last_name":"Taylor"}],"external_id":{"pmid":["36805026"]},"abstract":[{"text":"Type I CRISPR-Cas systems employ multi-subunit Cascade effector complexes to target foreign nucleic acids for destruction. Here, we present structures of D. vulgaris type I-C Cascade at various stages of double-stranded (ds)DNA target capture, revealing mechanisms that underpin PAM recognition and Cascade allosteric activation. We uncover an interesting mechanism of non-target strand (NTS) DNA stabilization via stacking interactions with the “belly” subunits, securing the NTS in place. This “molecular seatbelt” mechanism facilitates efficient R-loop formation and prevents dsDNA reannealing. Additionally, we provide structural insights into how two anti-CRISPR (Acr) proteins utilize distinct strategies to achieve a shared mechanism of type I-C Cascade inhibition by blocking PAM scanning. These observations form a structural basis for directional R-loop formation and reveal how different Acr proteins have converged upon common molecular mechanisms to efficiently shut down CRISPR immunity.","lang":"eng"}],"extern":"1","_id":"15129","oa_version":"Published Version","article_type":"original","page":"746-758.e5","oa":1}]