[{"article_processing_charge":"No","article_number":"2111.13693","date_updated":"2024-10-14T12:27:49Z","abstract":[{"text":"The world is structured in countless ways. It may be prudent to enforce corresponding structural properties to a learning algorithm's solution, such as incorporating prior beliefs, natural constraints, or causal structures. Doing so may translate to faster, more accurate, and more flexible models, which may directly relate to real-world impact. In this dissertation, we consider two different research areas that concern structuring a learning algorithm's solution: when the structure is known and when it has to be discovered.","lang":"eng"}],"department":[{"_id":"FrLo"}],"title":"Enforcing and discovering structure in machine learning","oa":1,"_id":"14221","doi":"10.48550/arXiv.2111.13693","citation":{"ama":"Locatello F. Enforcing and discovering structure in machine learning. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2111.13693\">10.48550/arXiv.2111.13693</a>","short":"F. Locatello, ArXiv (n.d.).","ieee":"F. Locatello, “Enforcing and discovering structure in machine learning,” <i>arXiv</i>. .","apa":"Locatello, F. (n.d.). Enforcing and discovering structure in machine learning. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2111.13693\">https://doi.org/10.48550/arXiv.2111.13693</a>","chicago":"Locatello, Francesco. “Enforcing and Discovering Structure in Machine Learning.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2111.13693\">https://doi.org/10.48550/arXiv.2111.13693</a>.","mla":"Locatello, Francesco. “Enforcing and Discovering Structure in Machine Learning.” <i>ArXiv</i>, 2111.13693, doi:<a href=\"https://doi.org/10.48550/arXiv.2111.13693\">10.48550/arXiv.2111.13693</a>.","ista":"Locatello F. Enforcing and discovering structure in machine learning. arXiv, 2111.13693."},"date_created":"2023-08-22T14:23:35Z","day":"26","publication_status":"submitted","type":"preprint","year":"2021","oa_version":"Preprint","language":[{"iso":"eng"}],"publication":"arXiv","arxiv":1,"month":"11","date_published":"2021-11-26T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"first_name":"Francesco","last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683"}],"external_id":{"arxiv":["2111.13693"]},"extern":"1","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2111.13693","open_access":"1"}],"status":"public"},{"status":"public","extern":"1","author":[{"first_name":"Frederik","last_name":"Träuble","full_name":"Träuble, Frederik"},{"last_name":"Dittadi","full_name":"Dittadi, Andrea","first_name":"Andrea"},{"full_name":"Wuthrich, Manuel","last_name":"Wuthrich","first_name":"Manuel"},{"first_name":"Felix","full_name":"Widmaier, Felix","last_name":"Widmaier"},{"first_name":"Peter Vincent","last_name":"Gehler","full_name":"Gehler, Peter Vincent"},{"full_name":"Winther, Ole","last_name":"Winther","first_name":"Ole"},{"full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","first_name":"Francesco"},{"last_name":"Bachem","full_name":"Bachem, Olivier","first_name":"Olivier"},{"last_name":"Schölkopf","full_name":"Schölkopf, Bernhard","first_name":"Bernhard"},{"full_name":"Bauer, Stefan","last_name":"Bauer","first_name":"Stefan"}],"date_published":"2021-07-23T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","month":"07","language":[{"iso":"eng"}],"publication":"ICML 2021 Workshop on Unsupervised Reinforcement Learning","year":"2021","oa_version":"None","type":"conference","publication_status":"published","day":"23","quality_controlled":"1","citation":{"short":"F. Träuble, A. Dittadi, M. Wuthrich, F. Widmaier, P.V. Gehler, O. Winther, F. Locatello, O. Bachem, B. Schölkopf, S. Bauer, in:, ICML 2021 Workshop on Unsupervised Reinforcement Learning, 2021.","ieee":"F. Träuble <i>et al.</i>, “Representation learning for out-of-distribution generalization in reinforcement learning,” in <i>ICML 2021 Workshop on Unsupervised Reinforcement Learning</i>, Virtual, 2021.","ama":"Träuble F, Dittadi A, Wuthrich M, et al. Representation learning for out-of-distribution generalization in reinforcement learning. In: <i>ICML 2021 Workshop on Unsupervised Reinforcement Learning</i>. ; 2021.","ista":"Träuble F, Dittadi A, Wuthrich M, Widmaier F, Gehler PV, Winther O, Locatello F, Bachem O, Schölkopf B, Bauer S. 2021. Representation learning for out-of-distribution generalization in reinforcement learning. ICML 2021 Workshop on Unsupervised Reinforcement Learning. ICML: International Conference on Machine Learning.","chicago":"Träuble, Frederik, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, and Stefan Bauer. “Representation Learning for Out-of-Distribution Generalization in Reinforcement Learning.” In <i>ICML 2021 Workshop on Unsupervised Reinforcement Learning</i>, 2021.","apa":"Träuble, F., Dittadi, A., Wuthrich, M., Widmaier, F., Gehler, P. V., Winther, O., … Bauer, S. (2021). Representation learning for out-of-distribution generalization in reinforcement learning. In <i>ICML 2021 Workshop on Unsupervised Reinforcement Learning</i>. Virtual.","mla":"Träuble, Frederik, et al. “Representation Learning for Out-of-Distribution Generalization in Reinforcement Learning.” <i>ICML 2021 Workshop on Unsupervised Reinforcement Learning</i>, 2021."},"date_created":"2023-09-13T12:43:14Z","_id":"14332","abstract":[{"text":"Learning data representations that are useful for various downstream tasks is a cornerstone of artificial intelligence. While existing methods are typically evaluated on downstream tasks such as classification or generative image quality, we propose to assess representations through their usefulness in downstream control tasks, such as reaching or pushing objects. By training over 10,000 reinforcement learning policies, we extensively evaluate to what extent different representation properties affect out-of-distribution (OOD) generalization. Finally, we demonstrate zero-shot transfer of these policies from simulation to the real world, without any domain randomization or fine-tuning. This paper aims to establish the first systematic characterization of the usefulness of learned representations for real-world OOD downstream tasks.","lang":"eng"}],"title":"Representation learning for out-of-distribution generalization in reinforcement learning","department":[{"_id":"FrLo"}],"conference":{"start_date":"2021-07-23","end_date":"2021-07-23","location":"Virtual","name":"ICML: International Conference on Machine Learning"},"date_updated":"2023-09-13T12:44:00Z","article_processing_charge":"No"},{"scopus_import":"1","date_created":"2023-03-26T22:01:09Z","citation":{"ista":"Bansal S, Chatterjee K, Vardi MY. 2021. On satisficing in quantitative games. 27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems. TACAS: Tools and Algorithms for the Construction and Analysis of Systems, LNCS, vol. 12651, 20–37.","chicago":"Bansal, Suguman, Krishnendu Chatterjee, and Moshe Y. Vardi. “On Satisficing in Quantitative Games.” In <i>27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems</i>, 12651:20–37. Springer Nature, 2021. <a href=\"https://doi.org/10.1007/978-3-030-72016-2_2\">https://doi.org/10.1007/978-3-030-72016-2_2</a>.","apa":"Bansal, S., Chatterjee, K., &#38; Vardi, M. Y. (2021). On satisficing in quantitative games. In <i>27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems</i> (Vol. 12651, pp. 20–37). Luxembourg City, Luxembourg: Springer Nature. <a href=\"https://doi.org/10.1007/978-3-030-72016-2_2\">https://doi.org/10.1007/978-3-030-72016-2_2</a>","mla":"Bansal, Suguman, et al. “On Satisficing in Quantitative Games.” <i>27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems</i>, vol. 12651, Springer Nature, 2021, pp. 20–37, doi:<a href=\"https://doi.org/10.1007/978-3-030-72016-2_2\">10.1007/978-3-030-72016-2_2</a>.","ama":"Bansal S, Chatterjee K, Vardi MY. On satisficing in quantitative games. In: <i>27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems</i>. Vol 12651. Springer Nature; 2021:20-37. doi:<a href=\"https://doi.org/10.1007/978-3-030-72016-2_2\">10.1007/978-3-030-72016-2_2</a>","ieee":"S. Bansal, K. Chatterjee, and M. Y. Vardi, “On satisficing in quantitative games,” in <i>27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems</i>, Luxembourg City, Luxembourg, 2021, vol. 12651, pp. 20–37.","short":"S. Bansal, K. Chatterjee, M.Y. Vardi, in:, 27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, Springer Nature, 2021, pp. 20–37."},"quality_controlled":"1","alternative_title":["LNCS"],"day":"21","intvolume":"     12651","doi":"10.1007/978-3-030-72016-2_2","ddc":["000"],"abstract":[{"lang":"eng","text":"Several problems in planning and reactive synthesis can be reduced to the analysis of two-player quantitative graph games. Optimization is one form of analysis. We argue that in many cases it may be better to replace the optimization problem with the satisficing problem, where instead of searching for optimal solutions, the goal is to search for solutions that adhere to a given threshold bound.\r\nThis work defines and investigates the satisficing problem on a two-player graph game with the discounted-sum cost model. We show that while the satisficing problem can be solved using numerical methods just like the optimization problem, this approach does not render compelling benefits over optimization. When the discount factor is, however, an integer, we present another approach to satisficing, which is purely based on automata methods. We show that this approach is algorithmically more performant – both theoretically and empirically – and demonstrates the broader applicability of satisficing over optimization."}],"file_date_updated":"2023-03-28T11:00:33Z","oa":1,"article_processing_charge":"No","conference":{"start_date":"2021-03-27","end_date":"2021-04-01","name":"TACAS: Tools and Algorithms for the Construction and Analysis of Systems","location":"Luxembourg City, Luxembourg"},"has_accepted_license":"1","status":"public","acknowledgement":"We thank anonymous reviewers for valuable inputs. This work is supported in part by NSF grant 2030859 to the CRA for the CIFellows Project, NSF grants IIS-1527668, CCF-1704883, IIS-1830549, the ERC CoG 863818 (ForM-SMArt), and an award from the Maryland Procurement Office.","file":[{"date_updated":"2023-03-28T11:00:33Z","relation":"main_file","creator":"dernst","file_id":"12777","file_size":747418,"file_name":"2021_LNCS_Bansal.pdf","success":1,"access_level":"open_access","content_type":"application/pdf","date_created":"2023-03-28T11:00:33Z","checksum":"b020b78b23587ce7610b1aafb4e63438"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2021-03-21T00:00:00Z","author":[{"full_name":"Bansal, Suguman","last_name":"Bansal","first_name":"Suguman"},{"full_name":"Chatterjee, Krishnendu","orcid":"0000-0002-4561-241X","last_name":"Chatterjee","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","first_name":"Krishnendu"},{"first_name":"Moshe Y.","full_name":"Vardi, Moshe Y.","last_name":"Vardi"}],"external_id":{"arxiv":["2101.02594"]},"volume":12651,"language":[{"iso":"eng"}],"publication":"27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems","page":"20-37","year":"2021","publication_identifier":{"issn":["0302-9743"],"eissn":["1611-3349"],"isbn":["9783030720155"]},"ec_funded":1,"_id":"12767","title":"On satisficing in quantitative games","tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"department":[{"_id":"KrCh"}],"date_updated":"2025-07-10T13:18:02Z","project":[{"call_identifier":"H2020","grant_number":"863818","name":"Formal Methods for Stochastic Models: Algorithms and Applications","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E"}],"month":"03","arxiv":1,"publication_status":"published","publisher":"Springer Nature","type":"conference","oa_version":"Published Version"},{"article_processing_charge":"No","date_updated":"2025-04-15T06:54:54Z","department":[{"_id":"EdHa"}],"tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"title":"Source data for the manuscript \"Theory of branching morphogenesis by local interactions and global guidance\"","ddc":["570"],"abstract":[{"lang":"eng","text":"The zip file includes source data used in the main text of the manuscript \"Theory of branching morphogenesis by local interactions and global guidance\", as well as a representative Jupyter notebook to reproduce the main figures. A sample script for the simulations of branching and annihilating random walks is also included (Sample_script_for_simulations_of_BARWs.ipynb) to generate exemplary branched networks under external guidance. A detailed description of the simulation setup is provided in the supplementary information of the manuscipt."}],"oa":1,"related_material":{"record":[{"id":"10402","relation":"used_in_publication","status":"public"}]},"_id":"13058","doi":"10.5281/ZENODO.5257160","citation":{"ista":"Ucar MC. 2021. Source data for the manuscript ‘Theory of branching morphogenesis by local interactions and global guidance’, Zenodo, <a href=\"https://doi.org/10.5281/ZENODO.5257160\">10.5281/ZENODO.5257160</a>.","apa":"Ucar, M. C. (2021). Source data for the manuscript “Theory of branching morphogenesis by local interactions and global guidance.” Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.5257160\">https://doi.org/10.5281/ZENODO.5257160</a>","chicago":"Ucar, Mehmet C. “Source Data for the Manuscript ‘Theory of Branching Morphogenesis by Local Interactions and Global Guidance.’” Zenodo, 2021. <a href=\"https://doi.org/10.5281/ZENODO.5257160\">https://doi.org/10.5281/ZENODO.5257160</a>.","mla":"Ucar, Mehmet C. <i>Source Data for the Manuscript “Theory of Branching Morphogenesis by Local Interactions and Global Guidance.”</i> Zenodo, 2021, doi:<a href=\"https://doi.org/10.5281/ZENODO.5257160\">10.5281/ZENODO.5257160</a>.","short":"M.C. Ucar, (2021).","ieee":"M. C. Ucar, “Source data for the manuscript ‘Theory of branching morphogenesis by local interactions and global guidance.’” Zenodo, 2021.","ama":"Ucar MC. Source data for the manuscript “Theory of branching morphogenesis by local interactions and global guidance.” 2021. doi:<a href=\"https://doi.org/10.5281/ZENODO.5257160\">10.5281/ZENODO.5257160</a>"},"date_created":"2023-05-23T13:46:34Z","corr_author":"1","day":"25","type":"research_data_reference","publisher":"Zenodo","oa_version":"Published Version","year":"2021","month":"08","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2021-08-25T00:00:00Z","author":[{"orcid":"0000-0003-0506-4217","full_name":"Ucar, Mehmet C","last_name":"Ucar","id":"50B2A802-6007-11E9-A42B-EB23E6697425","first_name":"Mehmet C"}],"main_file_link":[{"url":"https://doi.org/10.5281/zenodo.5257161","open_access":"1"}],"status":"public"},{"type":"research_data_reference","publisher":"Dryad","oa_version":"Published Version","year":"2021","date_published":"2021-10-29T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","project":[{"grant_number":"771402","call_identifier":"H2020","name":"Epidemics in ant societies on a chip","_id":"2649B4DE-B435-11E9-9278-68D0E5697425"}],"month":"10","author":[{"id":"351ED2AA-F248-11E8-B48F-1D18A9856A87","last_name":"Casillas Perez","full_name":"Casillas Perez, Barbara E","first_name":"Barbara E"},{"id":"3C7F4840-F248-11E8-B48F-1D18A9856A87","last_name":"Pull","full_name":"Pull, Christopher","orcid":"0000-0003-1122-3982","first_name":"Christopher"},{"last_name":"Naiser","full_name":"Naiser, Filip","first_name":"Filip"},{"full_name":"Naderlinger, Elisabeth","last_name":"Naderlinger","first_name":"Elisabeth"},{"first_name":"Jiri","full_name":"Matas, Jiri","last_name":"Matas"},{"first_name":"Sylvia","last_name":"Cremer","id":"2F64EC8C-F248-11E8-B48F-1D18A9856A87","full_name":"Cremer, Sylvia","orcid":"0000-0002-2193-3868"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.5061/dryad.7pvmcvdtj"}],"status":"public","date_updated":"2025-04-14T13:55:31Z","article_processing_charge":"No","tmp":{"name":"Creative Commons Public Domain Dedication (CC0 1.0)","image":"/images/cc_0.png","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","short":"CC0 (1.0)"},"license":"https://creativecommons.org/publicdomain/zero/1.0/","department":[{"_id":"SyCr"}],"ddc":["570"],"title":"Early queen infection shapes developmental dynamics and induces long-term disease protection in incipient ant colonies","abstract":[{"text":"Infections early in life can have enduring effects on an organism’s development and immunity. In this study, we show that this equally applies to developing “superorganisms” – incipient social insect colonies. When we exposed newly mated Lasius niger ant queens to a low pathogen dose, their colonies grew more slowly than controls before winter, but reached similar sizes afterwards. Independent of exposure, queen hibernation survival improved when the ratio of pupae to workers was small. Queens that reared fewer pupae before worker emergence exhibited lower pathogen levels, indicating that high brood rearing efforts interfere with the ability of the queen’s immune system to suppress pathogen proliferation. Early-life queen pathogen-exposure also improved the immunocompetence of her worker offspring, as demonstrated by challenging the workers to the same pathogen a year later. Transgenerational transfer of the queen’s pathogen experience to her workforce can hence durably reduce the disease susceptibility of the whole superorganism.","lang":"eng"}],"oa":1,"_id":"13061","related_material":{"record":[{"id":"10284","relation":"used_in_publication","status":"public"}]},"ec_funded":1,"doi":"10.5061/DRYAD.7PVMCVDTJ","date_created":"2023-05-23T16:14:35Z","citation":{"mla":"Casillas Perez, Barbara E., et al. <i>Early Queen Infection Shapes Developmental Dynamics and Induces Long-Term Disease Protection in Incipient Ant Colonies</i>. Dryad, 2021, doi:<a href=\"https://doi.org/10.5061/DRYAD.7PVMCVDTJ\">10.5061/DRYAD.7PVMCVDTJ</a>.","apa":"Casillas Perez, B. E., Pull, C., Naiser, F., Naderlinger, E., Matas, J., &#38; Cremer, S. (2021). Early queen infection shapes developmental dynamics and induces long-term disease protection in incipient ant colonies. Dryad. <a href=\"https://doi.org/10.5061/DRYAD.7PVMCVDTJ\">https://doi.org/10.5061/DRYAD.7PVMCVDTJ</a>","chicago":"Casillas Perez, Barbara E, Christopher Pull, Filip Naiser, Elisabeth Naderlinger, Jiri Matas, and Sylvia Cremer. “Early Queen Infection Shapes Developmental Dynamics and Induces Long-Term Disease Protection in Incipient Ant Colonies.” Dryad, 2021. <a href=\"https://doi.org/10.5061/DRYAD.7PVMCVDTJ\">https://doi.org/10.5061/DRYAD.7PVMCVDTJ</a>.","ista":"Casillas Perez BE, Pull C, Naiser F, Naderlinger E, Matas J, Cremer S. 2021. Early queen infection shapes developmental dynamics and induces long-term disease protection in incipient ant colonies, Dryad, <a href=\"https://doi.org/10.5061/DRYAD.7PVMCVDTJ\">10.5061/DRYAD.7PVMCVDTJ</a>.","ama":"Casillas Perez BE, Pull C, Naiser F, Naderlinger E, Matas J, Cremer S. Early queen infection shapes developmental dynamics and induces long-term disease protection in incipient ant colonies. 2021. doi:<a href=\"https://doi.org/10.5061/DRYAD.7PVMCVDTJ\">10.5061/DRYAD.7PVMCVDTJ</a>","ieee":"B. E. Casillas Perez, C. Pull, F. Naiser, E. Naderlinger, J. Matas, and S. Cremer, “Early queen infection shapes developmental dynamics and induces long-term disease protection in incipient ant colonies.” Dryad, 2021.","short":"B.E. Casillas Perez, C. Pull, F. Naiser, E. Naderlinger, J. Matas, S. Cremer, (2021)."},"day":"29","corr_author":"1"},{"citation":{"apa":"Szep, E., Sachdeva, H., &#38; Barton, N. H. (2021). Supplementary code for: Polygenic local adaptation in metapopulations: A stochastic eco-evolutionary model. Dryad. <a href=\"https://doi.org/10.5061/DRYAD.8GTHT76P1\">https://doi.org/10.5061/DRYAD.8GTHT76P1</a>","mla":"Szep, Eniko, et al. <i>Supplementary Code for: Polygenic Local Adaptation in Metapopulations: A Stochastic Eco-Evolutionary Model</i>. Dryad, 2021, doi:<a href=\"https://doi.org/10.5061/DRYAD.8GTHT76P1\">10.5061/DRYAD.8GTHT76P1</a>.","chicago":"Szep, Eniko, Himani Sachdeva, and Nicholas H Barton. “Supplementary Code for: Polygenic Local Adaptation in Metapopulations: A Stochastic Eco-Evolutionary Model.” Dryad, 2021. <a href=\"https://doi.org/10.5061/DRYAD.8GTHT76P1\">https://doi.org/10.5061/DRYAD.8GTHT76P1</a>.","ista":"Szep E, Sachdeva H, Barton NH. 2021. Supplementary code for: Polygenic local adaptation in metapopulations: A stochastic eco-evolutionary model, Dryad, <a href=\"https://doi.org/10.5061/DRYAD.8GTHT76P1\">10.5061/DRYAD.8GTHT76P1</a>.","ama":"Szep E, Sachdeva H, Barton NH. Supplementary code for: Polygenic local adaptation in metapopulations: A stochastic eco-evolutionary model. 2021. doi:<a href=\"https://doi.org/10.5061/DRYAD.8GTHT76P1\">10.5061/DRYAD.8GTHT76P1</a>","short":"E. Szep, H. Sachdeva, N.H. Barton, (2021).","ieee":"E. Szep, H. Sachdeva, and N. H. Barton, “Supplementary code for: Polygenic local adaptation in metapopulations: A stochastic eco-evolutionary model.” Dryad, 2021."},"date_created":"2023-05-23T16:17:02Z","day":"02","corr_author":"1","_id":"13062","related_material":{"record":[{"id":"9252","relation":"used_in_publication","status":"public"}]},"doi":"10.5061/DRYAD.8GTHT76P1","abstract":[{"text":"This paper analyzes the conditions for local adaptation in a metapopulation with infinitely many islands under a model of hard selection, where population size depends on local fitness. Each island belongs to one of two distinct ecological niches or habitats. Fitness is influenced by an additive trait which is under habitat-dependent directional selection. Our analysis is based on the diffusion approximation and  accounts for both genetic drift and demographic stochasticity. By neglecting linkage disequilibria, it yields the joint distribution of allele frequencies and population size on each island. We find that under hard selection, the conditions for local adaptation in a rare habitat are more restrictive for more polygenic traits: even moderate migration load per locus at very many loci is sufficient for population sizes to decline. This further reduces the efficacy of selection at individual loci due to increased drift and because smaller populations are more prone to swamping due to migration, causing a positive feedback between increasing maladaptation and declining population sizes. Our analysis also highlights the importance of demographic stochasticity, which  exacerbates the decline in numbers of maladapted populations, leading to population collapse in the rare habitat at significantly lower migration than predicted by deterministic arguments.","lang":"eng"}],"tmp":{"name":"Creative Commons Public Domain Dedication (CC0 1.0)","image":"/images/cc_0.png","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","short":"CC0 (1.0)"},"department":[{"_id":"NiBa"}],"title":"Supplementary code for: Polygenic local adaptation in metapopulations: A stochastic eco-evolutionary model","ddc":["570"],"oa":1,"article_processing_charge":"No","date_updated":"2025-06-12T06:35:39Z","main_file_link":[{"url":"https://doi.org/10.5061/dryad.8gtht76p1","open_access":"1"}],"status":"public","month":"03","date_published":"2021-03-02T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"id":"485BB5A4-F248-11E8-B48F-1D18A9856A87","last_name":"Szep","full_name":"Szep, Eniko","first_name":"Eniko"},{"first_name":"Himani","full_name":"Sachdeva, Himani","last_name":"Sachdeva","id":"42377A0A-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","last_name":"Barton","full_name":"Barton, Nicholas H","orcid":"0000-0002-8548-5240"}],"type":"research_data_reference","publisher":"Dryad","oa_version":"Published Version","year":"2021"},{"doi":"10.5061/dryad.sqv9s4n51","related_material":{"link":[{"relation":"software","url":"https://github.com/medical-genomics-group/gmrm"}],"record":[{"id":"8429","relation":"used_in_publication","status":"public"}]},"_id":"13063","corr_author":"1","day":"04","date_created":"2023-05-23T16:20:16Z","citation":{"ista":"Robinson MR. 2021. Probabilistic inference of the genetic architecture of functional enrichment of complex traits, Dryad, <a href=\"https://doi.org/10.5061/dryad.sqv9s4n51\">10.5061/dryad.sqv9s4n51</a>.","apa":"Robinson, M. R. (2021). Probabilistic inference of the genetic architecture of functional enrichment of complex traits. Dryad. <a href=\"https://doi.org/10.5061/dryad.sqv9s4n51\">https://doi.org/10.5061/dryad.sqv9s4n51</a>","mla":"Robinson, Matthew Richard. <i>Probabilistic Inference of the Genetic Architecture of Functional Enrichment of Complex Traits</i>. Dryad, 2021, doi:<a href=\"https://doi.org/10.5061/dryad.sqv9s4n51\">10.5061/dryad.sqv9s4n51</a>.","chicago":"Robinson, Matthew Richard. “Probabilistic Inference of the Genetic Architecture of Functional Enrichment of Complex Traits.” Dryad, 2021. <a href=\"https://doi.org/10.5061/dryad.sqv9s4n51\">https://doi.org/10.5061/dryad.sqv9s4n51</a>.","short":"M.R. Robinson, (2021).","ieee":"M. R. Robinson, “Probabilistic inference of the genetic architecture of functional enrichment of complex traits.” Dryad, 2021.","ama":"Robinson MR. Probabilistic inference of the genetic architecture of functional enrichment of complex traits. 2021. doi:<a href=\"https://doi.org/10.5061/dryad.sqv9s4n51\">10.5061/dryad.sqv9s4n51</a>"},"date_updated":"2025-06-12T06:54:51Z","article_processing_charge":"No","oa":1,"title":"Probabilistic inference of the genetic architecture of functional enrichment of complex traits","tmp":{"name":"Creative Commons Public Domain Dedication (CC0 1.0)","image":"/images/cc_0.png","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","short":"CC0 (1.0)"},"ddc":["570"],"abstract":[{"text":"We develop a Bayesian model (BayesRR-RC) that provides robust SNP-heritability estimation, an alternative to marker discovery, and accurate genomic prediction, taking 22 seconds per iteration to estimate 8.4 million SNP-effects and 78 SNP-heritability parameters in the UK Biobank. We find that only $\\leq$ 10\\% of the genetic variation captured for height, body mass index, cardiovascular disease, and type 2 diabetes is attributable to proximal regulatory regions within 10kb upstream of genes, while 12-25% is attributed to coding regions, 32-44% to introns, and 22-28% to distal 10-500kb upstream regions. Up to 24% of all cis and coding regions of each chromosome are associated with each trait, with over 3,100 independent exonic and intronic regions and over 5,400 independent regulatory regions having &gt;95% probability of contributing &gt;0.001% to the genetic variance of these four traits. Our open-source software (GMRM) provides a scalable alternative to current approaches for biobank data.","lang":"eng"}],"department":[{"_id":"MaRo"}],"author":[{"last_name":"Robinson","id":"E5D42276-F5DA-11E9-8E24-6303E6697425","orcid":"0000-0001-8982-8813","full_name":"Robinson, Matthew Richard","first_name":"Matthew Richard"}],"date_published":"2021-11-04T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","month":"11","status":"public","main_file_link":[{"url":"https://doi.org/10.5061/dryad.sqv9s4n51","open_access":"1"}],"year":"2021","oa_version":"Published Version","type":"research_data_reference","publisher":"Dryad"},{"doi":"10.5281/ZENODO.5148117","_id":"13068","related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"12217"}]},"day":"30","citation":{"mla":"Randriamanantsoa, Samuel, et al. <i>Spatiotemporal Dynamics of Self-Organized Branching in Pancreas-Derived Organoids</i>. Zenodo, 2021, doi:<a href=\"https://doi.org/10.5281/ZENODO.5148117\">10.5281/ZENODO.5148117</a>.","apa":"Randriamanantsoa, S., Papargyriou, A., Maurer, C., Peschke, K., Schuster, M., Zecchin, G., … Bausch, A. R. (2021). Spatiotemporal dynamics of self-organized branching in pancreas-derived organoids. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.5148117\">https://doi.org/10.5281/ZENODO.5148117</a>","chicago":"Randriamanantsoa, Samuel, Aristeidis Papargyriou, Carlo Maurer, Katja Peschke, Maximilian Schuster, Giulia Zecchin, Katja Steiger, et al. “Spatiotemporal Dynamics of Self-Organized Branching in Pancreas-Derived Organoids.” Zenodo, 2021. <a href=\"https://doi.org/10.5281/ZENODO.5148117\">https://doi.org/10.5281/ZENODO.5148117</a>.","ista":"Randriamanantsoa S, Papargyriou A, Maurer C, Peschke K, Schuster M, Zecchin G, Steiger K, Öllinger R, Saur D, Scheel C, Rad R, Hannezo EB, Reichert M, Bausch AR. 2021. Spatiotemporal dynamics of self-organized branching in pancreas-derived organoids, Zenodo, <a href=\"https://doi.org/10.5281/ZENODO.5148117\">10.5281/ZENODO.5148117</a>.","ieee":"S. Randriamanantsoa <i>et al.</i>, “Spatiotemporal dynamics of self-organized branching in pancreas-derived organoids.” Zenodo, 2021.","short":"S. Randriamanantsoa, A. Papargyriou, C. Maurer, K. Peschke, M. Schuster, G. Zecchin, K. Steiger, R. Öllinger, D. Saur, C. Scheel, R. Rad, E.B. Hannezo, M. Reichert, A.R. Bausch, (2021).","ama":"Randriamanantsoa S, Papargyriou A, Maurer C, et al. Spatiotemporal dynamics of self-organized branching in pancreas-derived organoids. 2021. doi:<a href=\"https://doi.org/10.5281/ZENODO.5148117\">10.5281/ZENODO.5148117</a>"},"date_created":"2023-05-23T16:39:24Z","date_updated":"2025-06-11T13:53:54Z","article_processing_charge":"No","oa":1,"tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"ddc":["570"],"abstract":[{"lang":"eng","text":"Source data and source code for the graphs in \"Spatiotemporal dynamics of self-organized branching pancreatic cancer-derived organoids\"."}],"title":"Spatiotemporal dynamics of self-organized branching in pancreas-derived organoids","department":[{"_id":"EdHa"}],"author":[{"last_name":"Randriamanantsoa","full_name":"Randriamanantsoa, Samuel","first_name":"Samuel"},{"first_name":"Aristeidis","full_name":"Papargyriou, Aristeidis","last_name":"Papargyriou"},{"first_name":"Carlo","last_name":"Maurer","full_name":"Maurer, Carlo"},{"last_name":"Peschke","full_name":"Peschke, Katja","first_name":"Katja"},{"full_name":"Schuster, Maximilian","last_name":"Schuster","first_name":"Maximilian"},{"last_name":"Zecchin","full_name":"Zecchin, Giulia","first_name":"Giulia"},{"last_name":"Steiger","full_name":"Steiger, Katja","first_name":"Katja"},{"first_name":"Rupert","full_name":"Öllinger, Rupert","last_name":"Öllinger"},{"last_name":"Saur","full_name":"Saur, Dieter","first_name":"Dieter"},{"full_name":"Scheel, Christina","last_name":"Scheel","first_name":"Christina"},{"first_name":"Roland","full_name":"Rad, Roland","last_name":"Rad"},{"full_name":"Hannezo, Edouard B","orcid":"0000-0001-6005-1561","last_name":"Hannezo","id":"3A9DB764-F248-11E8-B48F-1D18A9856A87","first_name":"Edouard B"},{"full_name":"Reichert, Maximilian","last_name":"Reichert","first_name":"Maximilian"},{"first_name":"Andreas R.","last_name":"Bausch","full_name":"Bausch, Andreas R."}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2021-07-30T00:00:00Z","month":"07","main_file_link":[{"url":"https://doi.org/10.5281/zenodo.6577226","open_access":"1"}],"status":"public","year":"2021","oa_version":"Published Version","publisher":"Zenodo","type":"research_data_reference"},{"date_updated":"2023-08-14T11:53:26Z","article_processing_charge":"No","oa":1,"title":"Neuronal HSF-1 coordinates the propagation of fat desaturation across tissues to enable adaptation to high temperatures in C. elegans","tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"department":[{"_id":"MaDe"}],"abstract":[{"text":"To survive elevated temperatures, ectotherms adjust the fluidity of membranes by fine-tuning lipid desaturation levels in a process previously described to be cell-autonomous. We have discovered that, in Caenorhabditis elegans, neuronal Heat shock Factor 1 (HSF-1), the conserved master regulator of the heat shock response (HSR)- causes extensive fat remodelling in peripheral tissues. These changes include a decrease in fat desaturase and acid lipase expression in the intestine, and a global shift in the saturation levels of plasma membrane’s phospholipids. The observed remodelling of plasma membrane is in line with ectothermic adaptive responses and gives worms a cumulative advantage to warm temperatures. We have determined that at least six TAX-2/TAX-4 cGMP gated channel expressing sensory neurons and TGF-β/BMP are required for signalling across tissues to modulate fat desaturation. We also find neuronal hsf-1  is not only sufficient but also partially necessary to control the fat remodelling response and for survival at warm temperatures. This is the first study to show that a thermostat-based mechanism can cell non-autonomously coordinate membrane saturation and composition across tissues in a multicellular animal.","lang":"eng"}],"ddc":["570"],"doi":"10.5281/ZENODO.5519410","related_material":{"record":[{"status":"public","relation":"used_in_publication","id":"10322"}]},"_id":"13069","day":"25","citation":{"ista":"Chauve L, Hodge F, Murdoch S, Masoudzadeh F, Mann H-J, Lopez-Clavijo A, Okkenhaug H, West G, Sousa BC, Segonds-Pichon A, Li C, Wingett S, Kienberger H, Kleigrewe K, de Bono M, Wakelam M, Casanueva O. 2021. Neuronal HSF-1 coordinates the propagation of fat desaturation across tissues to enable adaptation to high temperatures in C. elegans, Zenodo, <a href=\"https://doi.org/10.5281/ZENODO.5519410\">10.5281/ZENODO.5519410</a>.","mla":"Chauve, Laetitia, et al. <i>Neuronal HSF-1 Coordinates the Propagation of Fat Desaturation across Tissues to Enable Adaptation to High Temperatures in C. Elegans</i>. Zenodo, 2021, doi:<a href=\"https://doi.org/10.5281/ZENODO.5519410\">10.5281/ZENODO.5519410</a>.","apa":"Chauve, L., Hodge, F., Murdoch, S., Masoudzadeh, F., Mann, H.-J., Lopez-Clavijo, A., … Casanueva, O. (2021). Neuronal HSF-1 coordinates the propagation of fat desaturation across tissues to enable adaptation to high temperatures in C. elegans. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.5519410\">https://doi.org/10.5281/ZENODO.5519410</a>","chicago":"Chauve, Laetitia, Francesca Hodge, Sharlene Murdoch, Fatemah Masoudzadeh, Harry-Jack Mann, Andrea Lopez-Clavijo, Hanneke Okkenhaug, et al. “Neuronal HSF-1 Coordinates the Propagation of Fat Desaturation across Tissues to Enable Adaptation to High Temperatures in C. Elegans.” Zenodo, 2021. <a href=\"https://doi.org/10.5281/ZENODO.5519410\">https://doi.org/10.5281/ZENODO.5519410</a>.","ieee":"L. Chauve <i>et al.</i>, “Neuronal HSF-1 coordinates the propagation of fat desaturation across tissues to enable adaptation to high temperatures in C. elegans.” Zenodo, 2021.","short":"L. Chauve, F. Hodge, S. Murdoch, F. Masoudzadeh, H.-J. Mann, A. Lopez-Clavijo, H. Okkenhaug, G. West, B.C. Sousa, A. Segonds-Pichon, C. Li, S. Wingett, H. Kienberger, K. Kleigrewe, M. de Bono, M. Wakelam, O. Casanueva, (2021).","ama":"Chauve L, Hodge F, Murdoch S, et al. Neuronal HSF-1 coordinates the propagation of fat desaturation across tissues to enable adaptation to high temperatures in C. elegans. 2021. doi:<a href=\"https://doi.org/10.5281/ZENODO.5519410\">10.5281/ZENODO.5519410</a>"},"date_created":"2023-05-23T16:40:56Z","oa_version":"Published Version","year":"2021","type":"research_data_reference","publisher":"Zenodo","author":[{"last_name":"Chauve","full_name":"Chauve, Laetitia","first_name":"Laetitia"},{"last_name":"Hodge","full_name":"Hodge, Francesca","first_name":"Francesca"},{"full_name":"Murdoch, Sharlene","last_name":"Murdoch","first_name":"Sharlene"},{"last_name":"Masoudzadeh","full_name":"Masoudzadeh, Fatemah","first_name":"Fatemah"},{"first_name":"Harry-Jack","last_name":"Mann","full_name":"Mann, Harry-Jack"},{"last_name":"Lopez-Clavijo","full_name":"Lopez-Clavijo, Andrea","first_name":"Andrea"},{"first_name":"Hanneke","full_name":"Okkenhaug, Hanneke","last_name":"Okkenhaug"},{"full_name":"West, Greg","last_name":"West","first_name":"Greg"},{"first_name":"Bebiana C.","full_name":"Sousa, Bebiana C.","last_name":"Sousa"},{"last_name":"Segonds-Pichon","full_name":"Segonds-Pichon, Anne","first_name":"Anne"},{"last_name":"Li","full_name":"Li, Cheryl","first_name":"Cheryl"},{"full_name":"Wingett, Steven","last_name":"Wingett","first_name":"Steven"},{"first_name":"Hermine","full_name":"Kienberger, Hermine","last_name":"Kienberger"},{"full_name":"Kleigrewe, Karin","last_name":"Kleigrewe","first_name":"Karin"},{"first_name":"Mario","orcid":"0000-0001-8347-0443","full_name":"de Bono, Mario","last_name":"de Bono","id":"4E3FF80E-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Michael","last_name":"Wakelam","full_name":"Wakelam, Michael"},{"first_name":"Olivia","last_name":"Casanueva","full_name":"Casanueva, Olivia"}],"date_published":"2021-12-25T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","month":"12","main_file_link":[{"open_access":"1","url":"https://doi.org/10.5281/zenodo.5547464"}],"status":"public"},{"main_file_link":[{"open_access":"1","url":"https://doi.org/10.5281/zenodo.5794029"}],"status":"public","author":[{"last_name":"McCartney","full_name":"McCartney, Daniel L","first_name":"Daniel L"},{"last_name":"Hillary","full_name":"Hillary, Robert F","first_name":"Robert F"},{"full_name":"Conole, Eleanor LS","last_name":"Conole","first_name":"Eleanor LS"},{"full_name":"Trejo Banos, Daniel","last_name":"Trejo Banos","first_name":"Daniel"},{"first_name":"Danni A","last_name":"Gadd","full_name":"Gadd, Danni A"},{"last_name":"Walker","full_name":"Walker, Rosie M","first_name":"Rosie M"},{"full_name":"Nangle, Cliff","last_name":"Nangle","first_name":"Cliff"},{"first_name":"Robin","full_name":"Flaig, Robin","last_name":"Flaig"},{"first_name":"Archie","last_name":"Campbell","full_name":"Campbell, Archie"},{"full_name":"Murray, Alison D","last_name":"Murray","first_name":"Alison D"},{"full_name":"Munoz Maniega, Susana","last_name":"Munoz Maniega","first_name":"Susana"},{"first_name":"Maria","full_name":"del C Valdes-Hernandez, Maria","last_name":"del C Valdes-Hernandez"},{"first_name":"Mathew A","last_name":"Harris","full_name":"Harris, Mathew A"},{"first_name":"Mark E","last_name":"Bastin","full_name":"Bastin, Mark E"},{"first_name":"Joanna M","full_name":"Wardlaw, Joanna M","last_name":"Wardlaw"},{"full_name":"Harris, Sarah E","last_name":"Harris","first_name":"Sarah E"},{"last_name":"Porteous","full_name":"Porteous, David J","first_name":"David J"},{"full_name":"Tucker-Drob, Elliot M","last_name":"Tucker-Drob","first_name":"Elliot M"},{"first_name":"Andrew M","full_name":"McIntosh, Andrew M","last_name":"McIntosh"},{"first_name":"Kathryn L","last_name":"Evans","full_name":"Evans, Kathryn L"},{"last_name":"Deary","full_name":"Deary, Ian J","first_name":"Ian J"},{"first_name":"Simon R","last_name":"Cox","full_name":"Cox, Simon R"},{"first_name":"Matthew Richard","orcid":"0000-0001-8982-8813","full_name":"Robinson, Matthew Richard","last_name":"Robinson","id":"E5D42276-F5DA-11E9-8E24-6303E6697425"},{"full_name":"Marioni, Riccardo E","last_name":"Marioni","first_name":"Riccardo E"}],"month":"12","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2021-12-20T00:00:00Z","oa_version":"Published Version","year":"2021","type":"research_data_reference","publisher":"Zenodo","day":"20","date_created":"2023-05-23T16:46:20Z","citation":{"short":"D.L. McCartney, R.F. Hillary, E.L. Conole, D. Trejo Banos, D.A. Gadd, R.M. Walker, C. Nangle, R. Flaig, A. Campbell, A.D. Murray, S. Munoz Maniega, M. del C Valdes-Hernandez, M.A. Harris, M.E. Bastin, J.M. Wardlaw, S.E. Harris, D.J. Porteous, E.M. Tucker-Drob, A.M. McIntosh, K.L. Evans, I.J. Deary, S.R. Cox, M.R. Robinson, R.E. Marioni, (2021).","ieee":"D. L. McCartney <i>et al.</i>, “Blood-based epigenome-wide analyses of cognitive abilities.” Zenodo, 2021.","ama":"McCartney DL, Hillary RF, Conole EL, et al. Blood-based epigenome-wide analyses of cognitive abilities. 2021. doi:<a href=\"https://doi.org/10.5281/ZENODO.5794028\">10.5281/ZENODO.5794028</a>","apa":"McCartney, D. L., Hillary, R. F., Conole, E. L., Trejo Banos, D., Gadd, D. A., Walker, R. M., … Marioni, R. E. (2021). Blood-based epigenome-wide analyses of cognitive abilities. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.5794028\">https://doi.org/10.5281/ZENODO.5794028</a>","mla":"McCartney, Daniel L., et al. <i>Blood-Based Epigenome-Wide Analyses of Cognitive Abilities</i>. Zenodo, 2021, doi:<a href=\"https://doi.org/10.5281/ZENODO.5794028\">10.5281/ZENODO.5794028</a>.","chicago":"McCartney, Daniel L, Robert F Hillary, Eleanor LS Conole, Daniel Trejo Banos, Danni A Gadd, Rosie M Walker, Cliff Nangle, et al. “Blood-Based Epigenome-Wide Analyses of Cognitive Abilities.” Zenodo, 2021. <a href=\"https://doi.org/10.5281/ZENODO.5794028\">https://doi.org/10.5281/ZENODO.5794028</a>.","ista":"McCartney DL, Hillary RF, Conole EL, Trejo Banos D, Gadd DA, Walker RM, Nangle C, Flaig R, Campbell A, Murray AD, Munoz Maniega S, del C Valdes-Hernandez M, Harris MA, Bastin ME, Wardlaw JM, Harris SE, Porteous DJ, Tucker-Drob EM, McIntosh AM, Evans KL, Deary IJ, Cox SR, Robinson MR, Marioni RE. 2021. Blood-based epigenome-wide analyses of cognitive abilities, Zenodo, <a href=\"https://doi.org/10.5281/ZENODO.5794028\">10.5281/ZENODO.5794028</a>."},"doi":"10.5281/ZENODO.5794028","related_material":{"record":[{"status":"public","relation":"used_in_publication","id":"10702"}]},"_id":"13072","oa":1,"ddc":["570"],"tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"department":[{"_id":"MaRo"}],"title":"Blood-based epigenome-wide analyses of cognitive abilities","abstract":[{"text":"CpGs and corresponding mean weights for DNAm-based prediction of cognitive abilities (6 traits)","lang":"eng"}],"article_processing_charge":"No","date_updated":"2025-06-11T13:54:53Z"},{"month":"03","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2021-03-09T00:00:00Z","author":[{"first_name":"Denise","last_name":"Puglia","id":"4D495994-AE37-11E9-AC72-31CAE5697425","orcid":"0000-0003-1144-2763","full_name":"Puglia, Denise"},{"first_name":"Esteban","last_name":"Martinez","full_name":"Martinez, Esteban"},{"last_name":"Menard","full_name":"Menard, Gerbold","first_name":"Gerbold"},{"first_name":"Andreas","full_name":"Pöschl, Andreas","last_name":"Pöschl"},{"first_name":"Sergei","last_name":"Gronin","full_name":"Gronin, Sergei"},{"first_name":"Geoffrey","last_name":"Gardner","full_name":"Gardner, Geoffrey"},{"first_name":"Ray","last_name":"Kallaher","full_name":"Kallaher, Ray"},{"full_name":"Manfra, Michael","last_name":"Manfra","first_name":"Michael"},{"full_name":"Marcus, Charles","last_name":"Marcus","first_name":"Charles"},{"orcid":"0000-0003-2607-2363","full_name":"Higginbotham, Andrew P","last_name":"Higginbotham","id":"4AD6785A-F248-11E8-B48F-1D18A9856A87","first_name":"Andrew P"},{"full_name":"Casparis, Lucas","last_name":"Casparis","first_name":"Lucas"}],"status":"public","main_file_link":[{"url":"https://doi.org/10.5281/zenodo.4592460","open_access":"1"}],"type":"research_data_reference","publisher":"Zenodo","year":"2021","oa_version":"Published Version","related_material":{"link":[{"url":"https://github.com/caslu85/Induced-Gap-Closing-Shared/tree/1.1.3","relation":"software"}],"record":[{"status":"public","relation":"used_in_publication","id":"9570"}]},"_id":"13080","doi":"10.5281/ZENODO.4592435","date_created":"2023-05-23T17:11:28Z","citation":{"ama":"Puglia D, Martinez E, Menard G, et al. Data for ’Closing of the Induced Gap in a Hybrid Superconductor-Semiconductor Nanowire. 2021. doi:<a href=\"https://doi.org/10.5281/ZENODO.4592435\">10.5281/ZENODO.4592435</a>","ieee":"D. Puglia <i>et al.</i>, “Data for ’Closing of the Induced Gap in a Hybrid Superconductor-Semiconductor Nanowire.” Zenodo, 2021.","short":"D. Puglia, E. Martinez, G. Menard, A. Pöschl, S. Gronin, G. Gardner, R. Kallaher, M. Manfra, C. Marcus, A.P. Higginbotham, L. Casparis, (2021).","ista":"Puglia D, Martinez E, Menard G, Pöschl A, Gronin S, Gardner G, Kallaher R, Manfra M, Marcus C, Higginbotham AP, Casparis L. 2021. Data for ’Closing of the Induced Gap in a Hybrid Superconductor-Semiconductor Nanowire, Zenodo, <a href=\"https://doi.org/10.5281/ZENODO.4592435\">10.5281/ZENODO.4592435</a>.","chicago":"Puglia, Denise, Esteban Martinez, Gerbold Menard, Andreas Pöschl, Sergei Gronin, Geoffrey Gardner, Ray Kallaher, et al. “Data for ’Closing of the Induced Gap in a Hybrid Superconductor-Semiconductor Nanowire.” Zenodo, 2021. <a href=\"https://doi.org/10.5281/ZENODO.4592435\">https://doi.org/10.5281/ZENODO.4592435</a>.","mla":"Puglia, Denise, et al. <i>Data for ’Closing of the Induced Gap in a Hybrid Superconductor-Semiconductor Nanowire</i>. Zenodo, 2021, doi:<a href=\"https://doi.org/10.5281/ZENODO.4592435\">10.5281/ZENODO.4592435</a>.","apa":"Puglia, D., Martinez, E., Menard, G., Pöschl, A., Gronin, S., Gardner, G., … Casparis, L. (2021). Data for ’Closing of the Induced Gap in a Hybrid Superconductor-Semiconductor Nanowire. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.4592435\">https://doi.org/10.5281/ZENODO.4592435</a>"},"corr_author":"1","day":"09","article_processing_charge":"No","date_updated":"2025-07-10T12:01:53Z","abstract":[{"lang":"eng","text":"Data for the manuscript 'Closing of the Induced Gap in a Hybrid Superconductor-Semiconductor Nanowire' ([2006.01275] Closing of the Induced Gap in a Hybrid Superconductor-Semiconductor Nanowire (arxiv.org))\r\n\r\nWe upload a pdf with extended data sets, and the raw data for these extended datasets as well."}],"title":"Data for 'Closing of the Induced Gap in a Hybrid Superconductor-Semiconductor Nanowire","ddc":["530"],"department":[{"_id":"AnHi"}],"oa":1},{"file":[{"relation":"main_file","creator":"dernst","file_id":"13155","date_updated":"2023-06-19T10:49:12Z","access_level":"open_access","content_type":"application/pdf","date_created":"2023-06-19T10:49:12Z","checksum":"19489cf5e16a0596b1f92e317d97c9b0","file_size":591332,"success":1,"file_name":"2021_PMLR_Nguyen.pdf"}],"date_published":"2021-07-01T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","volume":139,"author":[{"first_name":"Quynh","last_name":"Nguyen","full_name":"Nguyen, Quynh"},{"last_name":"Mondelli","id":"27EB676C-8706-11E9-9510-7717E6697425","full_name":"Mondelli, Marco","orcid":"0000-0002-3242-7020","first_name":"Marco"},{"last_name":"Montufar","full_name":"Montufar, Guido","first_name":"Guido"}],"external_id":{"arxiv":["2012.11654"]},"status":"public","acknowledgement":"The authors would like to thank the anonymous reviewers for their helpful comments. MM was partially supported by the 2019 Lopez-Loreta Prize. QN and GM acknowledge support from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no 757983).","year":"2021","page":"8119-8129","publication":"Proceedings of the 38th International Conference on Machine Learning","language":[{"iso":"eng"}],"intvolume":"       139","quality_controlled":"1","citation":{"ama":"Nguyen Q, Mondelli M, Montufar G. Tight bounds on the smallest Eigenvalue of the neural tangent kernel for deep ReLU networks. In: <i>Proceedings of the 38th International Conference on Machine Learning</i>. Vol 139. ML Research Press; 2021:8119-8129.","short":"Q. Nguyen, M. Mondelli, G. Montufar, in:, Proceedings of the 38th International Conference on Machine Learning, ML Research Press, 2021, pp. 8119–8129.","ieee":"Q. Nguyen, M. Mondelli, and G. Montufar, “Tight bounds on the smallest Eigenvalue of the neural tangent kernel for deep ReLU networks,” in <i>Proceedings of the 38th International Conference on Machine Learning</i>, Virtual, 2021, vol. 139, pp. 8119–8129.","ista":"Nguyen Q, Mondelli M, Montufar G. 2021. Tight bounds on the smallest Eigenvalue of the neural tangent kernel for deep ReLU networks. Proceedings of the 38th International Conference on Machine Learning. ICML: International Conference on Machine Learning vol. 139, 8119–8129.","chicago":"Nguyen, Quynh, Marco Mondelli, and Guido Montufar. “Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks.” In <i>Proceedings of the 38th International Conference on Machine Learning</i>, 139:8119–29. ML Research Press, 2021.","apa":"Nguyen, Q., Mondelli, M., &#38; Montufar, G. (2021). Tight bounds on the smallest Eigenvalue of the neural tangent kernel for deep ReLU networks. In <i>Proceedings of the 38th International Conference on Machine Learning</i> (Vol. 139, pp. 8119–8129). Virtual: ML Research Press.","mla":"Nguyen, Quynh, et al. “Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks.” <i>Proceedings of the 38th International Conference on Machine Learning</i>, vol. 139, ML Research Press, 2021, pp. 8119–29."},"date_created":"2023-06-18T22:00:48Z","scopus_import":"1","day":"01","conference":{"start_date":"2021-07-18","location":"Virtual","name":"ICML: International Conference on Machine Learning","end_date":"2021-07-24"},"article_processing_charge":"No","has_accepted_license":"1","ddc":["000"],"abstract":[{"text":"A recent line of work has analyzed the theoretical properties of deep neural networks via the Neural Tangent Kernel (NTK). In particular, the smallest eigenvalue of the NTK has been related to the memorization capacity, the global convergence of gradient descent algorithms and the generalization of deep nets. However, existing results either provide bounds in the two-layer setting or assume that the spectrum of the NTK matrices is bounded away from 0 for multi-layer networks. In this paper, we provide tight bounds on the smallest eigenvalue of NTK matrices for deep ReLU nets, both in the limiting case of infinite widths and for finite widths. In the finite-width setting, the network architectures we consider are fairly general: we require the existence of a wide layer with roughly order of N neurons, N being the number of data samples; and the scaling of the remaining layer widths is arbitrary (up to logarithmic factors). To obtain our results, we analyze various quantities of independent interest: we give lower bounds on the smallest singular value of hidden feature matrices, and upper bounds on the Lipschitz constant of input-output feature maps.","lang":"eng"}],"oa":1,"file_date_updated":"2023-06-19T10:49:12Z","month":"07","project":[{"name":"Prix Lopez-Loretta 2019 - Marco Mondelli","_id":"059876FA-7A3F-11EA-A408-12923DDC885E"}],"publisher":"ML Research Press","type":"conference","publication_status":"published","oa_version":"Published Version","arxiv":1,"_id":"13146","publication_identifier":{"isbn":["9781713845065"],"eissn":["2640-3498"]},"date_updated":"2025-07-10T11:50:36Z","tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"department":[{"_id":"MaMo"}],"title":"Tight bounds on the smallest Eigenvalue of the neural tangent kernel for deep ReLU networks"},{"conference":{"start_date":"2021-07-18","end_date":"2021-07-24","name":"ICML: International Conference on Machine Learning","location":"Virtual"},"article_processing_charge":"No","has_accepted_license":"1","ddc":["000"],"abstract":[{"lang":"eng","text":"We investigate fast and communication-efficient algorithms for the classic problem of minimizing a sum of strongly convex and smooth functions that are distributed among n\r\n different nodes, which can communicate using a limited number of bits. Most previous communication-efficient approaches for this problem are limited to first-order optimization, and therefore have \\emph{linear} dependence on the condition number in their communication complexity. We show that this dependence is not inherent: communication-efficient methods can in fact have sublinear dependence on the condition number. For this, we design and analyze the first communication-efficient distributed variants of preconditioned gradient descent for Generalized Linear Models, and for Newton’s method. Our results rely on a new technique for quantizing both the preconditioner and the descent direction at each step of the algorithms, while controlling their convergence rate. We also validate our findings experimentally, showing faster convergence and reduced communication relative to previous methods."}],"oa":1,"file_date_updated":"2023-06-19T10:41:05Z","intvolume":"       139","citation":{"ama":"Alimisis F, Davies P, Alistarh D-A. Communication-efficient distributed optimization with quantized preconditioners. In: <i>Proceedings of the 38th International Conference on Machine Learning</i>. Vol 139. ML Research Press; 2021:196-206.","short":"F. Alimisis, P. Davies, D.-A. Alistarh, in:, Proceedings of the 38th International Conference on Machine Learning, ML Research Press, 2021, pp. 196–206.","ieee":"F. Alimisis, P. Davies, and D.-A. Alistarh, “Communication-efficient distributed optimization with quantized preconditioners,” in <i>Proceedings of the 38th International Conference on Machine Learning</i>, Virtual, 2021, vol. 139, pp. 196–206.","chicago":"Alimisis, Foivos, Peter Davies, and Dan-Adrian Alistarh. “Communication-Efficient Distributed Optimization with Quantized Preconditioners.” In <i>Proceedings of the 38th International Conference on Machine Learning</i>, 139:196–206. ML Research Press, 2021.","mla":"Alimisis, Foivos, et al. “Communication-Efficient Distributed Optimization with Quantized Preconditioners.” <i>Proceedings of the 38th International Conference on Machine Learning</i>, vol. 139, ML Research Press, 2021, pp. 196–206.","apa":"Alimisis, F., Davies, P., &#38; Alistarh, D.-A. (2021). Communication-efficient distributed optimization with quantized preconditioners. In <i>Proceedings of the 38th International Conference on Machine Learning</i> (Vol. 139, pp. 196–206). Virtual: ML Research Press.","ista":"Alimisis F, Davies P, Alistarh D-A. 2021. Communication-efficient distributed optimization with quantized preconditioners. Proceedings of the 38th International Conference on Machine Learning. ICML: International Conference on Machine Learning vol. 139, 196–206."},"quality_controlled":"1","date_created":"2023-06-18T22:00:48Z","scopus_import":"1","day":"01","corr_author":"1","year":"2021","language":[{"iso":"eng"}],"page":"196-206","publication":"Proceedings of the 38th International Conference on Machine Learning","date_published":"2021-07-01T00:00:00Z","file":[{"creator":"dernst","file_id":"13154","relation":"main_file","date_updated":"2023-06-19T10:41:05Z","checksum":"7ec0d59bac268b49c76bf2e036dedd7a","content_type":"application/pdf","access_level":"open_access","date_created":"2023-06-19T10:41:05Z","success":1,"file_name":"2021_PMLR_Alimisis.pdf","file_size":429087}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","volume":139,"author":[{"full_name":"Alimisis, Foivos","last_name":"Alimisis","first_name":"Foivos"},{"first_name":"Peter","id":"11396234-BB50-11E9-B24C-90FCE5697425","last_name":"Davies","orcid":"0000-0002-5646-9524","full_name":"Davies, Peter"},{"first_name":"Dan-Adrian","last_name":"Alistarh","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","full_name":"Alistarh, Dan-Adrian","orcid":"0000-0003-3650-940X"}],"external_id":{"arxiv":["2102.07214"]},"status":"public","acknowledgement":"The authors would like to thank Janne Korhonen, Aurelien Lucchi, Celestine MendlerDunner and Antonio Orvieto for helpful discussions. FA ¨and DA were supported during this work by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 805223 ScaleML). PD was supported by the European Union’s Horizon 2020 programme under the Marie Skłodowska-Curie grant agreement No. 754411.","date_updated":"2025-07-10T11:50:37Z","title":"Communication-efficient distributed optimization with quantized preconditioners","tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"department":[{"_id":"DaAl"}],"_id":"13147","ec_funded":1,"publication_identifier":{"isbn":["9781713845065"],"eissn":["2640-3498"]},"type":"conference","publication_status":"published","publisher":"ML Research Press","oa_version":"Published Version","arxiv":1,"project":[{"_id":"268A44D6-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","grant_number":"805223","name":"Elastic Coordination for Scalable Machine Learning"},{"call_identifier":"H2020","grant_number":"754411","name":"ISTplus - Postdoctoral Fellowships","_id":"260C2330-B435-11E9-9278-68D0E5697425"}],"month":"07"},{"issue":"12","publication":"Acta Physico-Chimica Sinica","language":[{"iso":"eng"}],"year":"2021","status":"public","volume":37,"external_id":{"isi":["000731879300002"]},"author":[{"first_name":"Cheng","orcid":"0000-0002-9515-4277","full_name":"Chang, Cheng","last_name":"Chang","id":"9E331C2E-9F27-11E9-AE48-5033E6697425"},{"last_name":"Chen","full_name":"Chen, Wei","first_name":"Wei"},{"first_name":"Ye","full_name":"Chen, Ye","last_name":"Chen"},{"first_name":"Yonghua","full_name":"Chen, Yonghua","last_name":"Chen"},{"full_name":"Chen, Yu","last_name":"Chen","first_name":"Yu"},{"full_name":"Ding, Feng","last_name":"Ding","first_name":"Feng"},{"full_name":"Fan, Chunhai","last_name":"Fan","first_name":"Chunhai"},{"full_name":"Fan, Hong Jin","last_name":"Fan","first_name":"Hong Jin"},{"last_name":"Fan","full_name":"Fan, Zhanxi","first_name":"Zhanxi"},{"first_name":"Cheng","full_name":"Gong, Cheng","last_name":"Gong"},{"first_name":"Yongji","full_name":"Gong, Yongji","last_name":"Gong"},{"first_name":"Qiyuan","last_name":"He","full_name":"He, Qiyuan"},{"last_name":"Hong","full_name":"Hong, Xun","first_name":"Xun"},{"first_name":"Sheng","last_name":"Hu","full_name":"Hu, Sheng"},{"first_name":"Weida","last_name":"Hu","full_name":"Hu, Weida"},{"first_name":"Wei","last_name":"Huang","full_name":"Huang, Wei"},{"full_name":"Huang, Yuan","last_name":"Huang","first_name":"Yuan"},{"first_name":"Wei","last_name":"Ji","full_name":"Ji, Wei"},{"full_name":"Li, Dehui","last_name":"Li","first_name":"Dehui"},{"first_name":"Lain Jong","last_name":"Li","full_name":"Li, Lain Jong"},{"last_name":"Li","full_name":"Li, Qiang","first_name":"Qiang"},{"first_name":"Li","last_name":"Lin","full_name":"Lin, Li"},{"full_name":"Ling, Chongyi","last_name":"Ling","first_name":"Chongyi"},{"first_name":"Minghua","last_name":"Liu","full_name":"Liu, Minghua"},{"first_name":"Nan","last_name":"Liu","full_name":"Liu, Nan"},{"full_name":"Liu, Zhuang","last_name":"Liu","first_name":"Zhuang"},{"full_name":"Loh, Kian Ping","last_name":"Loh","first_name":"Kian Ping"},{"first_name":"Jianmin","last_name":"Ma","full_name":"Ma, Jianmin"},{"first_name":"Feng","full_name":"Miao, Feng","last_name":"Miao"},{"last_name":"Peng","full_name":"Peng, Hailin","first_name":"Hailin"},{"first_name":"Mingfei","last_name":"Shao","full_name":"Shao, Mingfei"},{"full_name":"Song, Li","last_name":"Song","first_name":"Li"},{"first_name":"Shao","last_name":"Su","full_name":"Su, Shao"},{"last_name":"Sun","full_name":"Sun, Shuo","first_name":"Shuo"},{"last_name":"Tan","full_name":"Tan, Chaoliang","first_name":"Chaoliang"},{"first_name":"Zhiyong","full_name":"Tang, Zhiyong","last_name":"Tang"},{"full_name":"Wang, Dingsheng","last_name":"Wang","first_name":"Dingsheng"},{"first_name":"Huan","last_name":"Wang","full_name":"Wang, Huan"},{"last_name":"Wang","full_name":"Wang, Jinlan","first_name":"Jinlan"},{"last_name":"Wang","full_name":"Wang, Xin","first_name":"Xin"},{"last_name":"Wang","full_name":"Wang, Xinran","first_name":"Xinran"},{"full_name":"Wee, Andrew T.S.","last_name":"Wee","first_name":"Andrew T.S."},{"last_name":"Wei","full_name":"Wei, Zhongming","first_name":"Zhongming"},{"first_name":"Yuen","last_name":"Wu","full_name":"Wu, Yuen"},{"first_name":"Zhong Shuai","last_name":"Wu","full_name":"Wu, Zhong Shuai"},{"last_name":"Xiong","full_name":"Xiong, Jie","first_name":"Jie"},{"last_name":"Xiong","full_name":"Xiong, Qihua","first_name":"Qihua"},{"first_name":"Weigao","last_name":"Xu","full_name":"Xu, Weigao"},{"first_name":"Peng","last_name":"Yin","full_name":"Yin, Peng"},{"full_name":"Zeng, Haibo","last_name":"Zeng","first_name":"Haibo"},{"full_name":"Zeng, Zhiyuan","last_name":"Zeng","first_name":"Zhiyuan"},{"last_name":"Zhai","full_name":"Zhai, Tianyou","first_name":"Tianyou"},{"full_name":"Zhang, Han","last_name":"Zhang","first_name":"Han"},{"first_name":"Hui","last_name":"Zhang","full_name":"Zhang, Hui"},{"first_name":"Qichun","full_name":"Zhang, Qichun","last_name":"Zhang"},{"last_name":"Zhang","full_name":"Zhang, Tierui","first_name":"Tierui"},{"full_name":"Zhang, Xiang","last_name":"Zhang","first_name":"Xiang"},{"full_name":"Zhao, Li Dong","last_name":"Zhao","first_name":"Li Dong"},{"last_name":"Zhao","full_name":"Zhao, Meiting","first_name":"Meiting"},{"first_name":"Weijie","last_name":"Zhao","full_name":"Zhao, Weijie"},{"last_name":"Zhao","full_name":"Zhao, Yunxuan","first_name":"Yunxuan"},{"full_name":"Zhou, Kai Ge","last_name":"Zhou","first_name":"Kai Ge"},{"first_name":"Xing","full_name":"Zhou, Xing","last_name":"Zhou"},{"first_name":"Yu","last_name":"Zhou","full_name":"Zhou, Yu"},{"last_name":"Zhu","full_name":"Zhu, Hongwei","first_name":"Hongwei"},{"first_name":"Hua","full_name":"Zhang, Hua","last_name":"Zhang"},{"first_name":"Zhongfan","last_name":"Liu","full_name":"Liu, Zhongfan"}],"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","date_published":"2021-10-13T00:00:00Z","oa":1,"abstract":[{"lang":"eng","text":"Research on two-dimensional (2D) materials has been explosively increasing in last seventeen years in varying subjects including condensed matter physics, electronic engineering, materials science, and chemistry since the mechanical exfoliation of graphene in 2004. Starting from graphene, 2D materials now have become a big family with numerous members and diverse categories. The unique structural features and physicochemical properties of 2D materials make them one class of the most appealing candidates for a wide range of potential applications. In particular, we have seen some major breakthroughs made in the field of 2D materials in last five years not only in developing novel synthetic methods and exploring new structures/properties but also in identifying innovative applications and pushing forward commercialisation. In this review, we provide a critical summary on the recent progress made in the field of 2D materials with a particular focus on last five years. After a brief background introduction, we first discuss the major synthetic methods for 2D materials, including the mechanical exfoliation, liquid exfoliation, vapor phase deposition, and wet-chemical synthesis as well as phase engineering of 2D materials belonging to the field of phase engineering of nanomaterials (PEN). We then introduce the superconducting/optical/magnetic properties and chirality of 2D materials along with newly emerging magic angle 2D superlattices. Following that, the promising applications of 2D materials in electronics, optoelectronics, catalysis, energy storage, solar cells, biomedicine, sensors, environments, etc. are described sequentially. Thereafter, we present the theoretic calculations and simulations of 2D materials. Finally, after concluding the current progress, we provide some personal discussions on the existing challenges and future outlooks in this rapidly developing field. "}],"article_number":"2108017","article_processing_charge":"No","day":"13","citation":{"ieee":"C. Chang <i>et al.</i>, “Recent progress on two-dimensional materials,” <i>Acta Physico-Chimica Sinica</i>, vol. 37, no. 12. Peking University, 2021.","short":"C. Chang, W. Chen, Y. Chen, Y. Chen, Y. Chen, F. Ding, C. Fan, H.J. Fan, Z. Fan, C. Gong, Y. Gong, Q. He, X. Hong, S. Hu, W. Hu, W. Huang, Y. Huang, W. Ji, D. Li, L.J. Li, Q. Li, L. Lin, C. Ling, M. Liu, N. Liu, Z. Liu, K.P. Loh, J. Ma, F. Miao, H. Peng, M. Shao, L. Song, S. Su, S. Sun, C. Tan, Z. Tang, D. Wang, H. Wang, J. Wang, X. Wang, X. Wang, A.T.S. Wee, Z. Wei, Y. Wu, Z.S. Wu, J. Xiong, Q. Xiong, W. Xu, P. Yin, H. Zeng, Z. Zeng, T. Zhai, H. Zhang, H. Zhang, Q. Zhang, T. Zhang, X. Zhang, L.D. Zhao, M. Zhao, W. Zhao, Y. Zhao, K.G. Zhou, X. Zhou, Y. Zhou, H. Zhu, H. Zhang, Z. Liu, Acta Physico-Chimica Sinica 37 (2021).","ama":"Chang C, Chen W, Chen Y, et al. Recent progress on two-dimensional materials. <i>Acta Physico-Chimica Sinica</i>. 2021;37(12). doi:<a href=\"https://doi.org/10.3866/PKU.WHXB202108017\">10.3866/PKU.WHXB202108017</a>","apa":"Chang, C., Chen, W., Chen, Y., Chen, Y., Chen, Y., Ding, F., … Liu, Z. (2021). Recent progress on two-dimensional materials. <i>Acta Physico-Chimica Sinica</i>. Peking University. <a href=\"https://doi.org/10.3866/PKU.WHXB202108017\">https://doi.org/10.3866/PKU.WHXB202108017</a>","mla":"Chang, Cheng, et al. “Recent Progress on Two-Dimensional Materials.” <i>Acta Physico-Chimica Sinica</i>, vol. 37, no. 12, 2108017, Peking University, 2021, doi:<a href=\"https://doi.org/10.3866/PKU.WHXB202108017\">10.3866/PKU.WHXB202108017</a>.","chicago":"Chang, Cheng, Wei Chen, Ye Chen, Yonghua Chen, Yu Chen, Feng Ding, Chunhai Fan, et al. “Recent Progress on Two-Dimensional Materials.” <i>Acta Physico-Chimica Sinica</i>. Peking University, 2021. <a href=\"https://doi.org/10.3866/PKU.WHXB202108017\">https://doi.org/10.3866/PKU.WHXB202108017</a>.","ista":"Chang C, Chen W, Chen Y, Chen Y, Chen Y, Ding F, Fan C, Fan HJ, Fan Z, Gong C, Gong Y, He Q, Hong X, Hu S, Hu W, Huang W, Huang Y, Ji W, Li D, Li LJ, Li Q, Lin L, Ling C, Liu M, Liu N, Liu Z, Loh KP, Ma J, Miao F, Peng H, Shao M, Song L, Su S, Sun S, Tan C, Tang Z, Wang D, Wang H, Wang J, Wang X, Wang X, Wee ATS, Wei Z, Wu Y, Wu ZS, Xiong J, Xiong Q, Xu W, Yin P, Zeng H, Zeng Z, Zhai T, Zhang H, Zhang H, Zhang Q, Zhang T, Zhang X, Zhao LD, Zhao M, Zhao W, Zhao Y, Zhou KG, Zhou X, Zhou Y, Zhu H, Zhang H, Liu Z. 2021. Recent progress on two-dimensional materials. Acta Physico-Chimica Sinica. 37(12), 2108017."},"date_created":"2024-01-14T23:00:58Z","quality_controlled":"1","scopus_import":"1","doi":"10.3866/PKU.WHXB202108017","intvolume":"        37","oa_version":"Submitted Version","type":"journal_article","publication_status":"published","publisher":"Peking University","main_file_link":[{"url":"https://doi.org/10.3866/PKU.WHXB202108017","open_access":"1"}],"article_type":"review","month":"10","department":[{"_id":"MaIb"}],"title":"Recent progress on two-dimensional materials","date_updated":"2025-09-10T10:12:25Z","publication_identifier":{"issn":["1001-4861"]},"isi":1,"_id":"14800"},{"issue":"4","language":[{"iso":"eng"}],"publication":"Pure and Applied Analysis","page":"653-676","year":"2021","acknowledgement":"Financial support by the European Union’s Horizon 2020 research and innovation programme\r\nunder the Marie Skłodowska-Curie grant agreement No. 754411 (S.R.) and the European\r\nResearch Council under grant agreement No. 694227 (N.L. and R.S.), as well as by the SNSF\r\nEccellenza project PCEFP2 181153 (N.L.), the NCCR SwissMAP (N.L. and B.S.) and by the\r\nDeutsche Forschungsgemeinschaft (DFG) through the Research Training Group 1838: Spectral\r\nTheory and Dynamics of Quantum Systems (D.M.) is gratefully acknowledged. B.S. gratefully\r\nacknowledges financial support from the Swiss National Science Foundation through the Grant\r\n“Dynamical and energetic properties of Bose-Einstein condensates” and from the European\r\nResearch Council through the ERC-AdG CLaQS (grant agreement No 834782). D.M. thanks\r\nMarcel Griesemer for helpful discussions.","status":"public","author":[{"first_name":"Nikolai K","last_name":"Leopold","id":"4BC40BEC-F248-11E8-B48F-1D18A9856A87","full_name":"Leopold, Nikolai K","orcid":"0000-0002-0495-6822"},{"id":"cbddacee-2b11-11eb-a02e-a2e14d04e52d","last_name":"Mitrouskas","full_name":"Mitrouskas, David Johannes","first_name":"David Johannes"},{"first_name":"Simone Anna Elvira","full_name":"Rademacher, Simone Anna Elvira","orcid":"0000-0001-5059-4466","last_name":"Rademacher","id":"856966FE-A408-11E9-977E-802DE6697425"},{"last_name":"Schlein","full_name":"Schlein, Benjamin","first_name":"Benjamin"},{"first_name":"Robert","id":"4AFD0470-F248-11E8-B48F-1D18A9856A87","last_name":"Seiringer","full_name":"Seiringer, Robert","orcid":"0000-0002-6781-0521"}],"external_id":{"arxiv":["2005.02098"]},"volume":3,"date_published":"2021-10-01T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"abstract":[{"text":"We consider the Fröhlich Hamiltonian with large coupling constant α. For initial data of Pekar product form with coherent phonon field and with the electron minimizing the corresponding energy, we provide a norm approximation of the evolution, valid up to times of order α2. The approximation is given in terms of a Pekar product state, evolved through the Landau-Pekar equations, corrected by a Bogoliubov dynamics taking quantum fluctuations into account. This allows us to show that the Landau-Pekar equations approximately describe the evolution of the electron- and one-phonon reduced density matrices under the Fröhlich dynamics up to times of order α2.","lang":"eng"}],"article_processing_charge":"No","day":"01","corr_author":"1","scopus_import":"1","citation":{"chicago":"Leopold, Nikolai K, David Johannes Mitrouskas, Simone Anna Elvira Rademacher, Benjamin Schlein, and Robert Seiringer. “Landau–Pekar Equations and Quantum Fluctuations for the Dynamics of a Strongly Coupled Polaron.” <i>Pure and Applied Analysis</i>. Mathematical Sciences Publishers, 2021. <a href=\"https://doi.org/10.2140/paa.2021.3.653\">https://doi.org/10.2140/paa.2021.3.653</a>.","apa":"Leopold, N. K., Mitrouskas, D. J., Rademacher, S. A. E., Schlein, B., &#38; Seiringer, R. (2021). Landau–Pekar equations and quantum fluctuations for the dynamics of a strongly coupled polaron. <i>Pure and Applied Analysis</i>. Mathematical Sciences Publishers. <a href=\"https://doi.org/10.2140/paa.2021.3.653\">https://doi.org/10.2140/paa.2021.3.653</a>","mla":"Leopold, Nikolai K., et al. “Landau–Pekar Equations and Quantum Fluctuations for the Dynamics of a Strongly Coupled Polaron.” <i>Pure and Applied Analysis</i>, vol. 3, no. 4, Mathematical Sciences Publishers, 2021, pp. 653–76, doi:<a href=\"https://doi.org/10.2140/paa.2021.3.653\">10.2140/paa.2021.3.653</a>.","ista":"Leopold NK, Mitrouskas DJ, Rademacher SAE, Schlein B, Seiringer R. 2021. Landau–Pekar equations and quantum fluctuations for the dynamics of a strongly coupled polaron. Pure and Applied Analysis. 3(4), 653–676.","ama":"Leopold NK, Mitrouskas DJ, Rademacher SAE, Schlein B, Seiringer R. Landau–Pekar equations and quantum fluctuations for the dynamics of a strongly coupled polaron. <i>Pure and Applied Analysis</i>. 2021;3(4):653-676. doi:<a href=\"https://doi.org/10.2140/paa.2021.3.653\">10.2140/paa.2021.3.653</a>","ieee":"N. K. Leopold, D. J. Mitrouskas, S. A. E. Rademacher, B. Schlein, and R. Seiringer, “Landau–Pekar equations and quantum fluctuations for the dynamics of a strongly coupled polaron,” <i>Pure and Applied Analysis</i>, vol. 3, no. 4. Mathematical Sciences Publishers, pp. 653–676, 2021.","short":"N.K. Leopold, D.J. Mitrouskas, S.A.E. Rademacher, B. Schlein, R. Seiringer, Pure and Applied Analysis 3 (2021) 653–676."},"date_created":"2024-01-28T23:01:43Z","quality_controlled":"1","doi":"10.2140/paa.2021.3.653","intvolume":"         3","arxiv":1,"oa_version":"Preprint","publisher":"Mathematical Sciences Publishers","publication_status":"published","type":"journal_article","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2005.02098"}],"article_type":"original","month":"10","project":[{"name":"ISTplus - Postdoctoral Fellowships","call_identifier":"H2020","grant_number":"754411","_id":"260C2330-B435-11E9-9278-68D0E5697425"},{"_id":"25C6DC12-B435-11E9-9278-68D0E5697425","grant_number":"694227","call_identifier":"H2020","name":"Analysis of quantum many-body systems"}],"title":"Landau–Pekar equations and quantum fluctuations for the dynamics of a strongly coupled polaron","department":[{"_id":"RoSe"}],"date_updated":"2025-04-14T07:27:00Z","publication_identifier":{"eissn":["2578-5885"],"issn":["2578-5893"]},"ec_funded":1,"_id":"14889"},{"date_published":"2021-10-01T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"first_name":"Lea","orcid":"0000-0002-6854-1343","full_name":"Bossmann, Lea","last_name":"Bossmann","id":"A2E3BCBE-5FCC-11E9-AA4B-76F3E5697425"},{"full_name":"Petrat, Sören P","orcid":"0000-0002-9166-5889","last_name":"Petrat","id":"40AC02DC-F248-11E8-B48F-1D18A9856A87","first_name":"Sören P"},{"last_name":"Pickl","full_name":"Pickl, Peter","first_name":"Peter"},{"first_name":"Avy","full_name":"Soffer, Avy","last_name":"Soffer"}],"external_id":{"arxiv":["1912.11004"]},"volume":3,"status":"public","acknowledgement":"We are grateful for the hospitality of Central China Normal University (CCNU),\r\nwhere parts of this work were done, and thank Phan Th`anh Nam, Simone\r\nRademacher, Robert Seiringer and Stefan Teufel for helpful discussions. L.B. gratefully acknowledges the support by the German Research Foundation (DFG) within the Research\r\nTraining Group 1838 “Spectral Theory and Dynamics of Quantum Systems”, and the funding\r\nfrom the European Union’s Horizon 2020 research and innovation programme under the Marie\r\nSk lodowska-Curie Grant Agreement No. 754411.","year":"2021","page":"677-726","language":[{"iso":"eng"}],"publication":"Pure and Applied Analysis","issue":"4","intvolume":"         3","doi":"10.2140/paa.2021.3.677","scopus_import":"1","quality_controlled":"1","date_created":"2024-01-28T23:01:43Z","citation":{"mla":"Bossmann, Lea, et al. “Beyond Bogoliubov Dynamics.” <i>Pure and Applied Analysis</i>, vol. 3, no. 4, Mathematical Sciences Publishers, 2021, pp. 677–726, doi:<a href=\"https://doi.org/10.2140/paa.2021.3.677\">10.2140/paa.2021.3.677</a>.","apa":"Bossmann, L., Petrat, S. P., Pickl, P., &#38; Soffer, A. (2021). Beyond Bogoliubov dynamics. <i>Pure and Applied Analysis</i>. Mathematical Sciences Publishers. <a href=\"https://doi.org/10.2140/paa.2021.3.677\">https://doi.org/10.2140/paa.2021.3.677</a>","chicago":"Bossmann, Lea, Sören P Petrat, Peter Pickl, and Avy Soffer. “Beyond Bogoliubov Dynamics.” <i>Pure and Applied Analysis</i>. Mathematical Sciences Publishers, 2021. <a href=\"https://doi.org/10.2140/paa.2021.3.677\">https://doi.org/10.2140/paa.2021.3.677</a>.","ista":"Bossmann L, Petrat SP, Pickl P, Soffer A. 2021. Beyond Bogoliubov dynamics. Pure and Applied Analysis. 3(4), 677–726.","ieee":"L. Bossmann, S. P. Petrat, P. Pickl, and A. Soffer, “Beyond Bogoliubov dynamics,” <i>Pure and Applied Analysis</i>, vol. 3, no. 4. Mathematical Sciences Publishers, pp. 677–726, 2021.","short":"L. Bossmann, S.P. Petrat, P. Pickl, A. Soffer, Pure and Applied Analysis 3 (2021) 677–726.","ama":"Bossmann L, Petrat SP, Pickl P, Soffer A. Beyond Bogoliubov dynamics. <i>Pure and Applied Analysis</i>. 2021;3(4):677-726. doi:<a href=\"https://doi.org/10.2140/paa.2021.3.677\">10.2140/paa.2021.3.677</a>"},"day":"01","corr_author":"1","article_processing_charge":"No","abstract":[{"lang":"eng","text":"We consider a system of N interacting bosons in the mean-field scaling regime and construct corrections to the Bogoliubov dynamics that approximate the true N-body dynamics in norm to arbitrary precision. The N-independent corrections are given in terms of the solutions of the Bogoliubov and Hartree equations and satisfy a generalized form of Wick's theorem. We determine the n-point correlation functions of the excitations around the condensate, as well as the reduced densities of the N-body system, to arbitrary accuracy, given only the knowledge of the two-point functions of a quasi-free state and the solution of the Hartree equation. In this way, the complex problem of computing all n-point correlation functions for an interacting N-body system is essentially reduced to the problem of solving the Hartree equation and the PDEs for the Bogoliubov two-point functions."}],"oa":1,"project":[{"name":"ISTplus - Postdoctoral Fellowships","grant_number":"754411","call_identifier":"H2020","_id":"260C2330-B435-11E9-9278-68D0E5697425"}],"month":"10","article_type":"original","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.1912.11004","open_access":"1"}],"publisher":"Mathematical Sciences Publishers","publication_status":"published","type":"journal_article","oa_version":"Preprint","arxiv":1,"ec_funded":1,"_id":"14890","publication_identifier":{"issn":["2578-5893"],"eissn":["2578-5885"]},"date_updated":"2025-04-14T07:44:02Z","department":[{"_id":"RoSe"}],"title":"Beyond Bogoliubov dynamics"},{"publisher":"Wiley","type":"book_chapter","publication_status":"published","oa_version":"None","year":"2021","series_title":"eLS","publication":"Encyclopedia of Life Sciences","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2021-05-28T00:00:00Z","month":"05","volume":2,"author":[{"first_name":"Sean","id":"43161670-5719-11EA-8025-FABC3DDC885E","last_name":"Stankowski","full_name":"Stankowski, Sean"},{"first_name":"Daria","full_name":"Shipilina, Daria","orcid":"0000-0002-1145-9226","id":"428A94B0-F248-11E8-B48F-1D18A9856A87","last_name":"Shipilina"},{"full_name":"Westram, Anja M","orcid":"0000-0003-1050-4969","id":"3C147470-F248-11E8-B48F-1D18A9856A87","last_name":"Westram","first_name":"Anja M"}],"status":"public","date_updated":"2024-10-09T21:08:11Z","article_processing_charge":"No","abstract":[{"text":"Hybrid zones are narrow geographic regions where different populations, races or interbreeding species meet and mate, producing mixed ‘hybrid’ offspring. They are relatively common and can be found in a diverse range of organisms and environments. The study of hybrid zones has played an important role in our understanding of the origin of species, with hybrid zones having been described as ‘natural laboratories’. This is because they allow us to study,in situ, the conditions and evolutionary forces that enable divergent taxa to remain distinct despite some ongoing gene exchange between them.","lang":"eng"}],"title":"Hybrid Zones","department":[{"_id":"NiBa"}],"_id":"14984","intvolume":"         2","doi":"10.1002/9780470015902.a0029355","quality_controlled":"1","citation":{"ieee":"S. Stankowski, D. Shipilina, and A. M. Westram, “Hybrid Zones,” in <i>Encyclopedia of Life Sciences</i>, vol. 2, Wiley, 2021.","short":"S. Stankowski, D. Shipilina, A.M. Westram, in:, Encyclopedia of Life Sciences, Wiley, 2021.","ama":"Stankowski S, Shipilina D, Westram AM. Hybrid Zones. In: <i>Encyclopedia of Life Sciences</i>. Vol 2. eLS. Wiley; 2021. doi:<a href=\"https://doi.org/10.1002/9780470015902.a0029355\">10.1002/9780470015902.a0029355</a>","mla":"Stankowski, Sean, et al. “Hybrid Zones.” <i>Encyclopedia of Life Sciences</i>, vol. 2, Wiley, 2021, doi:<a href=\"https://doi.org/10.1002/9780470015902.a0029355\">10.1002/9780470015902.a0029355</a>.","apa":"Stankowski, S., Shipilina, D., &#38; Westram, A. M. (2021). Hybrid Zones. In <i>Encyclopedia of Life Sciences</i> (Vol. 2). Wiley. <a href=\"https://doi.org/10.1002/9780470015902.a0029355\">https://doi.org/10.1002/9780470015902.a0029355</a>","chicago":"Stankowski, Sean, Daria Shipilina, and Anja M Westram. “Hybrid Zones.” In <i>Encyclopedia of Life Sciences</i>, Vol. 2. ELS. Wiley, 2021. <a href=\"https://doi.org/10.1002/9780470015902.a0029355\">https://doi.org/10.1002/9780470015902.a0029355</a>.","ista":"Stankowski S, Shipilina D, Westram AM. 2021.Hybrid Zones. In: Encyclopedia of Life Sciences. vol. 2."},"date_created":"2024-02-14T12:05:50Z","corr_author":"1","day":"28","publication_identifier":{"isbn":["9780470016176"],"eisbn":["9780470015902"]}},{"place":"Cham","status":"public","author":[{"id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","last_name":"Lampert","orcid":"0000-0001-8622-7887","full_name":"Lampert, Christoph","first_name":"Christoph"}],"month":"10","date_published":"2021-10-13T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","edition":"2","page":"1395-1397","publication":"Computer Vision","language":[{"iso":"eng"}],"year":"2021","oa_version":"None","publication_status":"published","type":"book_chapter","publisher":"Springer","publication_identifier":{"eisbn":["9783030634162"],"isbn":["9783030634155"]},"corr_author":"1","day":"13","citation":{"ista":"Lampert C. 2021.Zero-Shot Learning. In: Computer Vision. , 1395–1397.","mla":"Lampert, Christoph. “Zero-Shot Learning.” <i>Computer Vision</i>, edited by Katsushi Ikeuchi, 2nd ed., Springer, 2021, pp. 1395–97, doi:<a href=\"https://doi.org/10.1007/978-3-030-63416-2_874\">10.1007/978-3-030-63416-2_874</a>.","chicago":"Lampert, Christoph. “Zero-Shot Learning.” In <i>Computer Vision</i>, edited by Katsushi Ikeuchi, 2nd ed., 1395–97. Cham: Springer, 2021. <a href=\"https://doi.org/10.1007/978-3-030-63416-2_874\">https://doi.org/10.1007/978-3-030-63416-2_874</a>.","apa":"Lampert, C. (2021). Zero-Shot Learning. In K. Ikeuchi (Ed.), <i>Computer Vision</i> (2nd ed., pp. 1395–1397). Cham: Springer. <a href=\"https://doi.org/10.1007/978-3-030-63416-2_874\">https://doi.org/10.1007/978-3-030-63416-2_874</a>","ama":"Lampert C. Zero-Shot Learning. In: Ikeuchi K, ed. <i>Computer Vision</i>. 2nd ed. Cham: Springer; 2021:1395-1397. doi:<a href=\"https://doi.org/10.1007/978-3-030-63416-2_874\">10.1007/978-3-030-63416-2_874</a>","ieee":"C. Lampert, “Zero-Shot Learning,” in <i>Computer Vision</i>, 2nd ed., K. Ikeuchi, Ed. Cham: Springer, 2021, pp. 1395–1397.","short":"C. Lampert, in:, K. Ikeuchi (Ed.), Computer Vision, 2nd ed., Springer, Cham, 2021, pp. 1395–1397."},"quality_controlled":"1","date_created":"2024-02-14T14:05:32Z","doi":"10.1007/978-3-030-63416-2_874","_id":"14987","editor":[{"full_name":"Ikeuchi, Katsushi","last_name":"Ikeuchi","first_name":"Katsushi"}],"title":"Zero-Shot Learning","department":[{"_id":"ChLa"}],"abstract":[{"text":"The goal of zero-shot learning is to construct a classifier that can identify object classes for which no training examples are available. When training data for some of the object classes is available but not for others, the name generalized zero-shot learning is commonly used.\r\nIn a wider sense, the phrase zero-shot is also used to describe other machine learning-based approaches that require no training data from the problem of interest, such as zero-shot action recognition or zero-shot machine translation.","lang":"eng"}],"article_processing_charge":"No","date_updated":"2024-10-09T21:08:12Z"},{"date_updated":"2025-05-14T09:25:33Z","article_processing_charge":"No","has_accepted_license":"1","tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"abstract":[{"text":"Raw data generated from the publication - The TPLATE complex mediates membrane bending during plant clathrin-mediated endocytosis by Johnson et al., 2021 In PNAS","lang":"eng"}],"ddc":["580"],"department":[{"_id":"JiFr"}],"title":"Raw data from Johnson et al, PNAS, 2021","oa":1,"_id":"14988","related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"9887"}]},"doi":"10.5281/ZENODO.5747100","citation":{"ieee":"A. J. Johnson, “Raw data from Johnson et al, PNAS, 2021.” Zenodo, 2021.","short":"A.J. Johnson, (2021).","ama":"Johnson AJ. Raw data from Johnson et al, PNAS, 2021. 2021. doi:<a href=\"https://doi.org/10.5281/ZENODO.5747100\">10.5281/ZENODO.5747100</a>","chicago":"Johnson, Alexander J. “Raw Data from Johnson et Al, PNAS, 2021.” Zenodo, 2021. <a href=\"https://doi.org/10.5281/ZENODO.5747100\">https://doi.org/10.5281/ZENODO.5747100</a>.","mla":"Johnson, Alexander J. <i>Raw Data from Johnson et Al, PNAS, 2021</i>. Zenodo, 2021, doi:<a href=\"https://doi.org/10.5281/ZENODO.5747100\">10.5281/ZENODO.5747100</a>.","apa":"Johnson, A. J. (2021). Raw data from Johnson et al, PNAS, 2021. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.5747100\">https://doi.org/10.5281/ZENODO.5747100</a>","ista":"Johnson AJ. 2021. Raw data from Johnson et al, PNAS, 2021, Zenodo, <a href=\"https://doi.org/10.5281/ZENODO.5747100\">10.5281/ZENODO.5747100</a>."},"date_created":"2024-02-14T14:13:48Z","corr_author":"1","day":"01","publisher":"Zenodo","type":"research_data_reference","oa_version":"Published Version","year":"2021","date_published":"2021-12-01T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","month":"12","author":[{"first_name":"Alexander J","id":"46A62C3A-F248-11E8-B48F-1D18A9856A87","last_name":"Johnson","full_name":"Johnson, Alexander J","orcid":"0000-0002-2739-8843"}],"status":"public","main_file_link":[{"url":"https://doi.org/10.5281/zenodo.5747100","open_access":"1"}]},{"abstract":[{"lang":"eng","text":"We consider random n×n matrices X with independent and centered entries and a general variance profile. We show that the spectral radius of X converges with very high probability to the square root of the spectral radius of the variance matrix of X when n tends to infinity. We also establish the optimal rate of convergence, that is a new result even for general i.i.d. matrices beyond the explicitly solvable Gaussian cases. The main ingredient is the proof of the local inhomogeneous circular law [arXiv:1612.07776] at the spectral edge."}],"oa":1,"article_processing_charge":"No","date_created":"2024-02-18T23:01:03Z","quality_controlled":"1","citation":{"apa":"Alt, J., Erdös, L., &#38; Krüger, T. H. (2021). Spectral radius of random matrices with independent entries. <i>Probability and Mathematical Physics</i>. Mathematical Sciences Publishers. <a href=\"https://doi.org/10.2140/pmp.2021.2.221\">https://doi.org/10.2140/pmp.2021.2.221</a>","mla":"Alt, Johannes, et al. “Spectral Radius of Random Matrices with Independent Entries.” <i>Probability and Mathematical Physics</i>, vol. 2, no. 2, Mathematical Sciences Publishers, 2021, pp. 221–80, doi:<a href=\"https://doi.org/10.2140/pmp.2021.2.221\">10.2140/pmp.2021.2.221</a>.","chicago":"Alt, Johannes, László Erdös, and Torben H Krüger. “Spectral Radius of Random Matrices with Independent Entries.” <i>Probability and Mathematical Physics</i>. Mathematical Sciences Publishers, 2021. <a href=\"https://doi.org/10.2140/pmp.2021.2.221\">https://doi.org/10.2140/pmp.2021.2.221</a>.","ista":"Alt J, Erdös L, Krüger TH. 2021. Spectral radius of random matrices with independent entries. Probability and Mathematical Physics. 2(2), 221–280.","ama":"Alt J, Erdös L, Krüger TH. Spectral radius of random matrices with independent entries. <i>Probability and Mathematical Physics</i>. 2021;2(2):221-280. doi:<a href=\"https://doi.org/10.2140/pmp.2021.2.221\">10.2140/pmp.2021.2.221</a>","short":"J. Alt, L. Erdös, T.H. Krüger, Probability and Mathematical Physics 2 (2021) 221–280.","ieee":"J. Alt, L. Erdös, and T. H. Krüger, “Spectral radius of random matrices with independent entries,” <i>Probability and Mathematical Physics</i>, vol. 2, no. 2. Mathematical Sciences Publishers, pp. 221–280, 2021."},"scopus_import":"1","corr_author":"1","day":"21","intvolume":"         2","doi":"10.2140/pmp.2021.2.221","publication":"Probability and Mathematical Physics","page":"221-280","language":[{"iso":"eng"}],"issue":"2","year":"2021","status":"public","acknowledgement":"Partially supported by ERC Starting Grant RandMat No. 715539 and the SwissMap grant of Swiss National Science Foundation. Partially supported by ERC Advanced Grant RanMat No. 338804. Partially supported by the Hausdorff Center for Mathematics in Bonn.","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2021-05-21T00:00:00Z","volume":2,"author":[{"first_name":"Johannes","id":"36D3D8B6-F248-11E8-B48F-1D18A9856A87","last_name":"Alt","full_name":"Alt, Johannes"},{"first_name":"László","full_name":"Erdös, László","orcid":"0000-0001-5366-9603","last_name":"Erdös","id":"4DBD5372-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0002-4821-3297","full_name":"Krüger, Torben H","last_name":"Krüger","id":"3020C786-F248-11E8-B48F-1D18A9856A87","first_name":"Torben H"}],"external_id":{"arxiv":["1907.13631"]},"department":[{"_id":"LaEr"}],"title":"Spectral radius of random matrices with independent entries","date_updated":"2025-04-15T08:05:02Z","publication_identifier":{"issn":["2690-0998"],"eissn":["2690-1005"]},"_id":"15013","ec_funded":1,"arxiv":1,"type":"journal_article","publisher":"Mathematical Sciences Publishers","publication_status":"published","oa_version":"Preprint","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.1907.13631"}],"month":"05","project":[{"call_identifier":"FP7","grant_number":"338804","name":"Random matrices, universality and disordered quantum systems","_id":"258DCDE6-B435-11E9-9278-68D0E5697425"}],"article_type":"original"}]