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The finding that the local environments characterising the different ice phases are found in water sheds light on water phase behaviors, and rationalizes the transferability of water models between different phases."}],"date_created":"2021-07-20T11:25:15Z","language":[{"iso":"eng"}],"citation":{"chicago":"Monserrat, Bartomeu, Jan Gerit Brandenburg, Edgar A. Engel, and Bingqing Cheng. “Extracting Ice Phases from Liquid Water: Why a Machine-Learning Water Model Generalizes so Well.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2006.13316\">https://doi.org/10.48550/arXiv.2006.13316</a>.","short":"B. Monserrat, J.G. Brandenburg, E.A. Engel, B. Cheng, ArXiv (n.d.).","ieee":"B. Monserrat, J. G. Brandenburg, E. A. Engel, and B. Cheng, “Extracting ice phases from liquid water: Why a machine-learning water model generalizes so well,” <i>arXiv</i>. .","mla":"Monserrat, Bartomeu, et al. “Extracting Ice Phases from Liquid Water: Why a Machine-Learning Water Model Generalizes so Well.” <i>ArXiv</i>, 2006.13316, doi:<a href=\"https://doi.org/10.48550/arXiv.2006.13316\">10.48550/arXiv.2006.13316</a>.","apa":"Monserrat, B., Brandenburg, J. G., Engel, E. A., &#38; Cheng, B. (n.d.). Extracting ice phases from liquid water: Why a machine-learning water model generalizes so well. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2006.13316\">https://doi.org/10.48550/arXiv.2006.13316</a>","ista":"Monserrat B, Brandenburg JG, Engel EA, Cheng B. Extracting ice phases from liquid water: Why a machine-learning water model generalizes so well. arXiv, 2006.13316.","ama":"Monserrat B, Brandenburg JG, Engel EA, Cheng B. Extracting ice phases from liquid water: Why a machine-learning water model generalizes so well. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2006.13316\">10.48550/arXiv.2006.13316</a>"},"doi":"10.48550/arXiv.2006.13316","article_processing_charge":"No","year":"2020","publication_status":"submitted","author":[{"full_name":"Monserrat, Bartomeu","first_name":"Bartomeu","last_name":"Monserrat"},{"last_name":"Brandenburg","first_name":"Jan Gerit","full_name":"Brandenburg, Jan Gerit"},{"last_name":"Engel","first_name":"Edgar A.","full_name":"Engel, Edgar A."},{"full_name":"Cheng, Bingqing","id":"cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9","first_name":"Bingqing","last_name":"Cheng","orcid":"0000-0002-3584-9632"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2024-10-14T12:05:56Z","date_published":"2020-06-23T00:00:00Z","article_number":"2006.13316","title":"Extracting ice phases from liquid water: Why a machine-learning water model generalizes so well","day":"23","arxiv":1,"type":"preprint","external_id":{"arxiv":["2006.13316"]},"oa":1},{"user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","other_data_license":"CC0 + CC BY (4.0)","title":"Additional file 2 of multi-method genome- and epigenome-wide studies of inflammatory protein levels in healthy older adults","date_updated":"2026-04-02T14:28:32Z","date_published":"2020-07-09T00:00:00Z","article_processing_charge":"No","year":"2020","author":[{"last_name":"Hillary","first_name":"Robert F.","full_name":"Hillary, Robert F."},{"first_name":"Daniel","last_name":"Trejo-Banos","full_name":"Trejo-Banos, Daniel"},{"full_name":"Kousathanas, Athanasios","last_name":"Kousathanas","first_name":"Athanasios"},{"full_name":"McCartney, Daniel L.","last_name":"McCartney","first_name":"Daniel L."},{"full_name":"Harris, Sarah E.","last_name":"Harris","first_name":"Sarah E."},{"full_name":"Stevenson, Anna J.","first_name":"Anna J.","last_name":"Stevenson"},{"full_name":"Patxot, Marion","first_name":"Marion","last_name":"Patxot"},{"full_name":"Ojavee, Sven Erik","last_name":"Ojavee","first_name":"Sven Erik"},{"last_name":"Zhang","first_name":"Qian","full_name":"Zhang, Qian"},{"full_name":"Liewald, David C.","first_name":"David C.","last_name":"Liewald"},{"last_name":"Ritchie","first_name":"Craig W.","full_name":"Ritchie, Craig W."},{"first_name":"Kathryn L.","last_name":"Evans","full_name":"Evans, Kathryn L."},{"full_name":"Tucker-Drob, Elliot M.","first_name":"Elliot M.","last_name":"Tucker-Drob"},{"full_name":"Wray, Naomi R.","last_name":"Wray","first_name":"Naomi R."},{"full_name":"McRae, Allan F. ","first_name":"Allan F. ","last_name":"McRae"},{"full_name":"Visscher, Peter M.","first_name":"Peter M.","last_name":"Visscher"},{"first_name":"Ian J.","last_name":"Deary","full_name":"Deary, Ian J."},{"id":"E5D42276-F5DA-11E9-8E24-6303E6697425","full_name":"Robinson, Matthew Richard","first_name":"Matthew Richard","orcid":"0000-0001-8982-8813","last_name":"Robinson"},{"full_name":"Marioni, Riccardo E. ","last_name":"Marioni","first_name":"Riccardo E. "}],"license":"https://creativecommons.org/licenses/by/4.0/","type":"research_data_reference","oa":1,"day":"09","related_material":{"record":[{"id":"8133","relation":"used_in_publication","status":"public"}]},"_id":"9706","status":"public","month":"07","oa_version":"Published Version","main_file_link":[{"url":"https://doi.org/10.6084/m9.figshare.12629697.v1","open_access":"1"}],"citation":{"mla":"Hillary, Robert F., et al. <i>Additional File 2 of Multi-Method Genome- and Epigenome-Wide Studies of Inflammatory Protein Levels in Healthy Older Adults</i>. Springer Nature, 2020, doi:<a href=\"https://doi.org/10.6084/m9.figshare.12629697.v1\">10.6084/m9.figshare.12629697.v1</a>.","ieee":"R. F. Hillary <i>et al.</i>, “Additional file 2 of multi-method genome- and epigenome-wide studies of inflammatory protein levels in healthy older adults.” Springer Nature, 2020.","ista":"Hillary RF, Trejo-Banos D, Kousathanas A, McCartney DL, Harris SE, Stevenson AJ, Patxot M, Ojavee SE, Zhang Q, Liewald DC, Ritchie CW, Evans KL, Tucker-Drob EM, Wray NR, McRae AF, Visscher PM, Deary IJ, Robinson MR, Marioni RE. 2020. Additional file 2 of multi-method genome- and epigenome-wide studies of inflammatory protein levels in healthy older adults, Springer Nature, <a href=\"https://doi.org/10.6084/m9.figshare.12629697.v1\">10.6084/m9.figshare.12629697.v1</a>.","apa":"Hillary, R. F., Trejo-Banos, D., Kousathanas, A., McCartney, D. L., Harris, S. E., Stevenson, A. J., … Marioni, R. E. (2020). Additional file 2 of multi-method genome- and epigenome-wide studies of inflammatory protein levels in healthy older adults. Springer Nature. <a href=\"https://doi.org/10.6084/m9.figshare.12629697.v1\">https://doi.org/10.6084/m9.figshare.12629697.v1</a>","ama":"Hillary RF, Trejo-Banos D, Kousathanas A, et al. Additional file 2 of multi-method genome- and epigenome-wide studies of inflammatory protein levels in healthy older adults. 2020. doi:<a href=\"https://doi.org/10.6084/m9.figshare.12629697.v1\">10.6084/m9.figshare.12629697.v1</a>","chicago":"Hillary, Robert F., Daniel Trejo-Banos, Athanasios Kousathanas, Daniel L. McCartney, Sarah E. Harris, Anna J. Stevenson, Marion Patxot, et al. “Additional File 2 of Multi-Method Genome- and Epigenome-Wide Studies of Inflammatory Protein Levels in Healthy Older Adults.” Springer Nature, 2020. <a href=\"https://doi.org/10.6084/m9.figshare.12629697.v1\">https://doi.org/10.6084/m9.figshare.12629697.v1</a>.","short":"R.F. Hillary, D. Trejo-Banos, A. Kousathanas, D.L. McCartney, S.E. Harris, A.J. Stevenson, M. Patxot, S.E. Ojavee, Q. Zhang, D.C. Liewald, C.W. Ritchie, K.L. Evans, E.M. Tucker-Drob, N.R. Wray, A.F. McRae, P.M. Visscher, I.J. Deary, M.R. Robinson, R.E. Marioni, (2020)."},"tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"doi":"10.6084/m9.figshare.12629697.v1","department":[{"_id":"MaRo"}],"date_created":"2021-07-23T08:59:15Z","has_accepted_license":"1","abstract":[{"lang":"eng","text":"Additional file 2: Supplementary Tables. The association of pre-adjusted protein levels with biological and technical covariates. Protein levels were adjusted for age, sex, array plate and four genetic principal components (population structure) prior to analyses. Significant associations are emboldened. (Table S1). pQTLs associated with inflammatory biomarker levels from Bayesian penalised regression model (Posterior Inclusion Probability > 95%). (Table S2). All pQTLs associated with inflammatory biomarker levels from ordinary least squares regression model (P < 7.14 × 10− 10). (Table S3). Summary of lambda values relating to ordinary least squares GWAS and EWAS performed on inflammatory protein levels (n = 70) in Lothian Birth Cohort 1936 study. (Table S4). Conditionally significant pQTLs associated with inflammatory biomarker levels from ordinary least squares regression model (P < 7.14 × 10− 10). (Table S5). Comparison of variance explained by ordinary least squares and Bayesian penalised regression models for concordantly identified SNPs. (Table S6). Estimate of heritability for blood protein levels as well as proportion of variance explained attributable to different prior mixtures. (Table S7). Comparison of heritability estimates from Ahsan et al. (maximum likelihood) and Hillary et al. (Bayesian penalised regression). (Table S8). List of concordant SNPs identified by linear model and Bayesian penalised regression and whether they have been previously identified as eQTLs. (Table S9). Bayesian tests of colocalisation for cis pQTLs and cis eQTLs. (Table S10). Sherlock algorithm: Genes whose expression are putatively associated with circulating inflammatory proteins that harbour pQTLs. (Table S11). CpGs associated with inflammatory protein biomarkers as identified by Bayesian model (Bayesian model; Posterior Inclusion Probability > 95%). (Table S12). CpGs associated with inflammatory protein biomarkers as identified by linear model (limma) at P < 5.14 × 10− 10. (Table S13). CpGs associated with inflammatory protein biomarkers as identified by mixed linear model (OSCA) at P < 5.14 × 10− 10. (Table S14). Estimate of variance explained for blood protein levels by DNA methylation as well as proportion of explained attributable to different prior mixtures - BayesR+. (Table S15). Comparison of variance in protein levels explained by genome-wide DNA methylation data by mixed linear model (OSCA) and Bayesian penalised regression model (BayesR+). (Table S16). Variance in circulating inflammatory protein biomarker levels explained by common genetic and methylation data (joint and conditional estimates from BayesR+). Ordered by combined variance explained by genetic and epigenetic data - smallest to largest. Significant results from t-tests comparing distributions for variance explained by methylation or genetics alone versus combined estimate are emboldened. (Table S17). Genetic and epigenetic factors identified by BayesR+ when conditioning on all SNPs and CpGs together. (Table S18). Mendelian Randomisation analyses to assess whether proteins with concordantly identified genetic signals are causally associated with Alzheimer’s disease risk. (Table S19)."}],"publisher":"Springer Nature"},{"tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"citation":{"ista":"Hartstein M, Hsu Y-T, Modic KA, Porras J, Loew T, Le Tacon M, Zuo H, Wang J, Zhu Z, Chan M, McDonald R, Lonzarich G, Keimer B, Sebastian S, Harrison N. 2020. Accompanying dataset for ‘Hard antinodal gap revealed by quantum oscillations in the pseudogap regime of underdoped high-Tc superconductors’, Apollo - University of Cambridge, <a href=\"https://doi.org/10.17863/cam.50169\">10.17863/cam.50169</a>.","ama":"Hartstein M, Hsu Y-T, Modic KA, et al. Accompanying dataset for “Hard antinodal gap revealed by quantum oscillations in the pseudogap regime of underdoped high-Tc superconductors.” 2020. doi:<a href=\"https://doi.org/10.17863/cam.50169\">10.17863/cam.50169</a>","apa":"Hartstein, M., Hsu, Y.-T., Modic, K. A., Porras, J., Loew, T., Le Tacon, M., … Harrison, N. (2020). Accompanying dataset for “Hard antinodal gap revealed by quantum oscillations in the pseudogap regime of underdoped high-Tc superconductors.” Apollo - University of Cambridge. <a href=\"https://doi.org/10.17863/cam.50169\">https://doi.org/10.17863/cam.50169</a>","mla":"Hartstein, Mate, et al. <i>Accompanying Dataset for “Hard Antinodal Gap Revealed by Quantum Oscillations in the Pseudogap Regime of Underdoped High-Tc Superconductors.”</i> Apollo - University of Cambridge, 2020, doi:<a href=\"https://doi.org/10.17863/cam.50169\">10.17863/cam.50169</a>.","ieee":"M. Hartstein <i>et al.</i>, “Accompanying dataset for ‘Hard antinodal gap revealed by quantum oscillations in the pseudogap regime of underdoped high-Tc superconductors.’” Apollo - University of Cambridge, 2020.","short":"M. Hartstein, Y.-T. Hsu, K.A. Modic, J. Porras, T. Loew, M. Le Tacon, H. Zuo, J. Wang, Z. Zhu, M. Chan, R. McDonald, G. Lonzarich, B. Keimer, S. Sebastian, N. Harrison, (2020).","chicago":"Hartstein, Mate, Yu-Te Hsu, Kimberly A Modic, Juan Porras, Toshinao Loew, Matthieu Le Tacon, Huakun Zuo, et al. “Accompanying Dataset for ‘Hard Antinodal Gap Revealed by Quantum Oscillations in the Pseudogap Regime of Underdoped High-Tc Superconductors.’” Apollo - University of Cambridge, 2020. <a href=\"https://doi.org/10.17863/cam.50169\">https://doi.org/10.17863/cam.50169</a>."},"doi":"10.17863/cam.50169","abstract":[{"lang":"eng","text":"This research data supports 'Hard antinodal gap revealed by quantum oscillations in the pseudogap regime of underdoped high-Tc superconductors'. A Readme file for plotting each figure is provided."}],"department":[{"_id":"KiMo"}],"has_accepted_license":"1","date_created":"2021-07-23T10:00:35Z","publisher":"Apollo - University of Cambridge","_id":"9708","main_file_link":[{"open_access":"1","url":"https://doi.org/10.17863/CAM.50169"}],"oa_version":"Published Version","status":"public","month":"05","type":"research_data_reference","oa":1,"related_material":{"record":[{"status":"public","id":"7942","relation":"used_in_publication"}]},"day":"29","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","date_updated":"2025-07-10T11:54:51Z","date_published":"2020-05-29T00:00:00Z","title":"Accompanying dataset for 'Hard antinodal gap revealed by quantum oscillations in the pseudogap regime of underdoped high-Tc superconductors'","article_processing_charge":"No","year":"2020","author":[{"last_name":"Hartstein","first_name":"Mate","full_name":"Hartstein, Mate"},{"full_name":"Hsu, Yu-Te","last_name":"Hsu","first_name":"Yu-Te"},{"full_name":"Modic, Kimberly A","id":"13C26AC0-EB69-11E9-87C6-5F3BE6697425","first_name":"Kimberly A","last_name":"Modic","orcid":"0000-0001-9760-3147"},{"full_name":"Porras, Juan","first_name":"Juan","last_name":"Porras"},{"last_name":"Loew","first_name":"Toshinao","full_name":"Loew, Toshinao"},{"last_name":"Le Tacon","first_name":"Matthieu","full_name":"Le Tacon, Matthieu"},{"last_name":"Zuo","first_name":"Huakun","full_name":"Zuo, Huakun"},{"full_name":"Wang, Jinhua","last_name":"Wang","first_name":"Jinhua"},{"full_name":"Zhu, Zengwei","last_name":"Zhu","first_name":"Zengwei"},{"first_name":"Mun","last_name":"Chan","full_name":"Chan, Mun"},{"first_name":"Ross","last_name":"McDonald","full_name":"McDonald, Ross"},{"last_name":"Lonzarich","first_name":"Gilbert","full_name":"Lonzarich, Gilbert"},{"first_name":"Bernhard","last_name":"Keimer","full_name":"Keimer, Bernhard"},{"full_name":"Sebastian, Suchitra","last_name":"Sebastian","first_name":"Suchitra"},{"full_name":"Harrison, Neil","first_name":"Neil","last_name":"Harrison"}]},{"type":"research_data_reference","related_material":{"record":[{"id":"7569","relation":"used_in_publication","status":"public"}]},"day":"25","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","date_updated":"2025-06-12T06:58:06Z","date_published":"2020-02-25T00:00:00Z","title":"Supporting information","article_processing_charge":"No","year":"2020","author":[{"id":"483E70DE-F248-11E8-B48F-1D18A9856A87","full_name":"Grah, Rok","first_name":"Rok","orcid":"0000-0003-2539-3560","last_name":"Grah"},{"full_name":"Friedlander, Tamar","last_name":"Friedlander","first_name":"Tamar"}],"doi":"10.1371/journal.pcbi.1007642.s001","citation":{"apa":"Grah, R., &#38; Friedlander, T. (2020). Supporting information. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1007642.s001\">https://doi.org/10.1371/journal.pcbi.1007642.s001</a>","ista":"Grah R, Friedlander T. 2020. Supporting information, Public Library of Science, <a href=\"https://doi.org/10.1371/journal.pcbi.1007642.s001\">10.1371/journal.pcbi.1007642.s001</a>.","ama":"Grah R, Friedlander T. Supporting information. 2020. doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1007642.s001\">10.1371/journal.pcbi.1007642.s001</a>","ieee":"R. Grah and T. Friedlander, “Supporting information.” Public Library of Science, 2020.","mla":"Grah, Rok, and Tamar Friedlander. <i>Supporting Information</i>. Public Library of Science, 2020, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1007642.s001\">10.1371/journal.pcbi.1007642.s001</a>.","short":"R. Grah, T. Friedlander, (2020).","chicago":"Grah, Rok, and Tamar Friedlander. “Supporting Information.” Public Library of Science, 2020. <a href=\"https://doi.org/10.1371/journal.pcbi.1007642.s001\">https://doi.org/10.1371/journal.pcbi.1007642.s001</a>."},"department":[{"_id":"GaTk"}],"date_created":"2021-08-06T07:15:04Z","publisher":"Public Library of Science","_id":"9776","month":"02","oa_version":"Published Version","status":"public"},{"type":"research_data_reference","oa":1,"day":"25","related_material":{"record":[{"status":"public","relation":"used_in_publication","id":"7569"}]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"Maximizing crosstalk","date_published":"2020-02-25T00:00:00Z","date_updated":"2025-06-12T06:58:06Z","article_processing_charge":"No","year":"2020","author":[{"id":"483E70DE-F248-11E8-B48F-1D18A9856A87","full_name":"Grah, Rok","first_name":"Rok","orcid":"0000-0003-2539-3560","last_name":"Grah"},{"full_name":"Friedlander, Tamar","last_name":"Friedlander","first_name":"Tamar"}],"doi":"10.1371/journal.pcbi.1007642.s002","citation":{"short":"R. Grah, T. Friedlander, (2020).","chicago":"Grah, Rok, and Tamar Friedlander. “Maximizing Crosstalk.” Public Library of Science, 2020. <a href=\"https://doi.org/10.1371/journal.pcbi.1007642.s002\">https://doi.org/10.1371/journal.pcbi.1007642.s002</a>.","ista":"Grah R, Friedlander T. 2020. Maximizing crosstalk, Public Library of Science, <a href=\"https://doi.org/10.1371/journal.pcbi.1007642.s002\">10.1371/journal.pcbi.1007642.s002</a>.","apa":"Grah, R., &#38; Friedlander, T. (2020). Maximizing crosstalk. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1007642.s002\">https://doi.org/10.1371/journal.pcbi.1007642.s002</a>","ama":"Grah R, Friedlander T. Maximizing crosstalk. 2020. doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1007642.s002\">10.1371/journal.pcbi.1007642.s002</a>","ieee":"R. Grah and T. Friedlander, “Maximizing crosstalk.” Public Library of Science, 2020.","mla":"Grah, Rok, and Tamar Friedlander. <i>Maximizing Crosstalk</i>. Public Library of Science, 2020, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1007642.s002\">10.1371/journal.pcbi.1007642.s002</a>."},"date_created":"2021-08-06T07:21:51Z","department":[{"_id":"GaTk"}],"publisher":"Public Library of Science","_id":"9777","month":"02","status":"public","oa_version":"None","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1371/journal.pcbi.1007642.s002"}]},{"doi":"10.1371/journal.pcbi.1007642.s003","citation":{"short":"R. Grah, T. Friedlander, (2020).","chicago":"Grah, Rok, and Tamar Friedlander. “Distribution of Crosstalk Values.” Public Library of Science, 2020. <a href=\"https://doi.org/10.1371/journal.pcbi.1007642.s003\">https://doi.org/10.1371/journal.pcbi.1007642.s003</a>.","apa":"Grah, R., &#38; Friedlander, T. (2020). Distribution of crosstalk values. 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(2020). CCDC 1991959: Experimental Crystal Structure Determination. CCDC. <a href=\"https://doi.org/10.5517/ccdc.csd.cc24vsrk\">https://doi.org/10.5517/ccdc.csd.cc24vsrk</a>","ama":"Schlemmer W, Nothdurft P, Petzold A, et al. CCDC 1991959: Experimental Crystal Structure Determination. 2020. doi:<a href=\"https://doi.org/10.5517/ccdc.csd.cc24vsrk\">10.5517/ccdc.csd.cc24vsrk</a>","ista":"Schlemmer W, Nothdurft P, Petzold A, Riess G, Frühwirt P, Schmallegger M, Gescheidt-Demner G, Fischer R, Freunberger SA, Kern W, Spirk S. 2020. CCDC 1991959: Experimental Crystal Structure Determination, CCDC, <a href=\"https://doi.org/10.5517/ccdc.csd.cc24vsrk\">10.5517/ccdc.csd.cc24vsrk</a>.","ieee":"W. Schlemmer <i>et al.</i>, “CCDC 1991959: Experimental Crystal Structure Determination.” CCDC, 2020.","mla":"Schlemmer, Werner, et al. <i>CCDC 1991959: Experimental Crystal Structure Determination</i>. CCDC, 2020, doi:<a href=\"https://doi.org/10.5517/ccdc.csd.cc24vsrk\">10.5517/ccdc.csd.cc24vsrk</a>.","short":"W. Schlemmer, P. Nothdurft, A. Petzold, G. Riess, P. Frühwirt, M. Schmallegger, G. Gescheidt-Demner, R. Fischer, S.A. Freunberger, W. Kern, S. Spirk, (2020).","chicago":"Schlemmer, Werner, Philipp Nothdurft, Alina Petzold, Gisbert Riess, Philipp Frühwirt, Max Schmallegger, Georg Gescheidt-Demner, et al. “CCDC 1991959: Experimental Crystal Structure Determination.” CCDC, 2020. <a href=\"https://doi.org/10.5517/ccdc.csd.cc24vsrk\">https://doi.org/10.5517/ccdc.csd.cc24vsrk</a>."},"doi":"10.5517/ccdc.csd.cc24vsrk","article_processing_charge":"No","year":"2020","author":[{"full_name":"Schlemmer, Werner","first_name":"Werner","last_name":"Schlemmer"},{"full_name":"Nothdurft, Philipp","first_name":"Philipp","last_name":"Nothdurft"},{"first_name":"Alina","last_name":"Petzold","full_name":"Petzold, Alina"},{"last_name":"Riess","first_name":"Gisbert","full_name":"Riess, Gisbert"},{"last_name":"Frühwirt","first_name":"Philipp","full_name":"Frühwirt, Philipp"},{"full_name":"Schmallegger, Max","last_name":"Schmallegger","first_name":"Max"},{"full_name":"Gescheidt-Demner, Georg","first_name":"Georg","last_name":"Gescheidt-Demner"},{"first_name":"Roland","last_name":"Fischer","full_name":"Fischer, Roland"},{"first_name":"Stefan Alexander","last_name":"Freunberger","orcid":"0000-0003-2902-5319","full_name":"Freunberger, Stefan Alexander","id":"A8CA28E6-CE23-11E9-AD2D-EC27E6697425"},{"last_name":"Kern","first_name":"Wolfgang","full_name":"Kern, Wolfgang"},{"full_name":"Spirk, Stefan","first_name":"Stefan","last_name":"Spirk"}],"user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","title":"CCDC 1991959: Experimental Crystal Structure Determination","date_updated":"2026-06-18T19:32:35Z","date_published":"2020-03-22T00:00:00Z","day":"22","related_material":{"record":[{"status":"public","id":"8329","relation":"used_in_publication"}]},"type":"research_data_reference","oa":1},{"month":"10","status":"public","oa_version":"Published Version","main_file_link":[{"open_access":"1","url":"https://doi.org/10.6084/m9.figshare.7957472.v1"}],"_id":"9798","doi":"10.6084/m9.figshare.7957472.v1","citation":{"ieee":"C. Fraisse and J. J. Welch, “Simulation code for Fig S2 from the distribution of epistasis on simple fitness landscapes.” Royal Society of London, 2020.","mla":"Fraisse, Christelle, and John J. Welch. <i>Simulation Code for Fig S2 from the Distribution of Epistasis on Simple Fitness Landscapes</i>. Royal Society of London, 2020, doi:<a href=\"https://doi.org/10.6084/m9.figshare.7957472.v1\">10.6084/m9.figshare.7957472.v1</a>.","ista":"Fraisse C, Welch JJ. 2020. Simulation code for Fig S2 from the distribution of epistasis on simple fitness landscapes, Royal Society of London, <a href=\"https://doi.org/10.6084/m9.figshare.7957472.v1\">10.6084/m9.figshare.7957472.v1</a>.","ama":"Fraisse C, Welch JJ. Simulation code for Fig S2 from the distribution of epistasis on simple fitness landscapes. 2020. doi:<a href=\"https://doi.org/10.6084/m9.figshare.7957472.v1\">10.6084/m9.figshare.7957472.v1</a>","apa":"Fraisse, C., &#38; Welch, J. J. (2020). Simulation code for Fig S2 from the distribution of epistasis on simple fitness landscapes. Royal Society of London. <a href=\"https://doi.org/10.6084/m9.figshare.7957472.v1\">https://doi.org/10.6084/m9.figshare.7957472.v1</a>","chicago":"Fraisse, Christelle, and John J. Welch. “Simulation Code for Fig S2 from the Distribution of Epistasis on Simple Fitness Landscapes.” Royal Society of London, 2020. <a href=\"https://doi.org/10.6084/m9.figshare.7957472.v1\">https://doi.org/10.6084/m9.figshare.7957472.v1</a>.","short":"C. Fraisse, J.J. Welch, (2020)."},"OA_type":"hybrid","publisher":"Royal Society of London","department":[{"_id":"BeVi"},{"_id":"NiBa"}],"date_created":"2021-08-06T11:18:15Z","abstract":[{"lang":"eng","text":"Fitness interactions between mutations can influence a population’s evolution in many different ways. While epistatic effects are difficult to measure precisely, important information is captured by the mean and variance of log fitnesses for individuals carrying different numbers of mutations. We derive predictions for these quantities from a class of simple fitness landscapes, based on models of optimizing selection on quantitative traits. We also explore extensions to the models, including modular pleiotropy, variable effect sizes, mutational bias and maladaptation of the wild type. We illustrate our approach by reanalysing a large dataset of mutant effects in a yeast snoRNA. Though characterized by some large epistatic effects, these data give a good overall fit to the non-epistatic null model, suggesting that epistasis might have limited influence on the evolutionary dynamics in this system. We also show how the amount of epistasis depends on both the underlying fitness landscape and the distribution of mutations, and so is expected to vary in consistent ways between new mutations, standing variation and fixed mutations."}],"title":"Simulation code for Fig S2 from the distribution of epistasis on simple fitness landscapes","date_updated":"2026-06-18T19:05:02Z","date_published":"2020-10-15T00:00:00Z","user_id":"0043cee0-e5fc-11ee-9736-f83bc23afbf0","author":[{"first_name":"Christelle","last_name":"Fraisse","orcid":"0000-0001-8441-5075","full_name":"Fraisse, Christelle","id":"32DF5794-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Welch","first_name":"John J.","full_name":"Welch, John J."}],"article_processing_charge":"No","year":"2020","oa":1,"OA_place":"publisher","type":"research_data_reference","day":"15","related_material":{"record":[{"status":"public","relation":"used_in_publication","id":"6467"}]}},{"author":[{"full_name":"Fraisse, Christelle","id":"32DF5794-F248-11E8-B48F-1D18A9856A87","first_name":"Christelle","last_name":"Fraisse","orcid":"0000-0001-8441-5075"},{"last_name":"Welch","first_name":"John J.","full_name":"Welch, John J."}],"article_processing_charge":"No","year":"2020","title":"Simulation code for Fig S1 from the distribution of epistasis on simple fitness landscapes","date_updated":"2026-06-18T19:05:02Z","date_published":"2020-10-15T00:00:00Z","user_id":"0043cee0-e5fc-11ee-9736-f83bc23afbf0","day":"15","related_material":{"record":[{"relation":"used_in_publication","id":"6467","status":"public"}]},"oa":1,"OA_place":"publisher","type":"research_data_reference","month":"10","status":"public","oa_version":"Published Version","main_file_link":[{"open_access":"1","url":"https://doi.org/10.6084/m9.figshare.7957469.v1"}],"_id":"9799","publisher":"Royal Society of London","date_created":"2021-08-06T11:26:57Z","department":[{"_id":"BeVi"},{"_id":"NiBa"}],"abstract":[{"text":"Fitness interactions between mutations can influence a population’s evolution in many different ways. While epistatic effects are difficult to measure precisely, important information is captured by the mean and variance of log fitnesses for individuals carrying different numbers of mutations. We derive predictions for these quantities from a class of simple fitness landscapes, based on models of optimizing selection on quantitative traits. We also explore extensions to the models, including modular pleiotropy, variable effect sizes, mutational bias and maladaptation of the wild type. We illustrate our approach by reanalysing a large dataset of mutant effects in a yeast snoRNA. Though characterized by some large epistatic effects, these data give a good overall fit to the non-epistatic null model, suggesting that epistasis might have limited influence on the evolutionary dynamics in this system. We also show how the amount of epistasis depends on both the underlying fitness landscape and the distribution of mutations, and so is expected to vary in consistent ways between new mutations, standing variation and fixed mutations.","lang":"eng"}],"citation":{"ieee":"C. Fraisse and J. J. Welch, “Simulation code for Fig S1 from the distribution of epistasis on simple fitness landscapes.” Royal Society of London, 2020.","mla":"Fraisse, Christelle, and John J. Welch. <i>Simulation Code for Fig S1 from the Distribution of Epistasis on Simple Fitness Landscapes</i>. Royal Society of London, 2020, doi:<a href=\"https://doi.org/10.6084/m9.figshare.7957469.v1\">10.6084/m9.figshare.7957469.v1</a>.","ama":"Fraisse C, Welch JJ. Simulation code for Fig S1 from the distribution of epistasis on simple fitness landscapes. 2020. doi:<a href=\"https://doi.org/10.6084/m9.figshare.7957469.v1\">10.6084/m9.figshare.7957469.v1</a>","apa":"Fraisse, C., &#38; Welch, J. J. (2020). Simulation code for Fig S1 from the distribution of epistasis on simple fitness landscapes. Royal Society of London. <a href=\"https://doi.org/10.6084/m9.figshare.7957469.v1\">https://doi.org/10.6084/m9.figshare.7957469.v1</a>","ista":"Fraisse C, Welch JJ. 2020. Simulation code for Fig S1 from the distribution of epistasis on simple fitness landscapes, Royal Society of London, <a href=\"https://doi.org/10.6084/m9.figshare.7957469.v1\">10.6084/m9.figshare.7957469.v1</a>.","chicago":"Fraisse, Christelle, and John J. Welch. “Simulation Code for Fig S1 from the Distribution of Epistasis on Simple Fitness Landscapes.” Royal Society of London, 2020. <a href=\"https://doi.org/10.6084/m9.figshare.7957469.v1\">https://doi.org/10.6084/m9.figshare.7957469.v1</a>.","short":"C. Fraisse, J.J. Welch, (2020)."},"doi":"10.6084/m9.figshare.7957469.v1","OA_type":"hybrid"},{"oa_version":"Preprint","quality_controlled":"1","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1806.08751"}],"_id":"6488","volume":9,"scopus_import":"1","department":[{"_id":"LaEr"}],"citation":{"short":"G. Cipolloni, L. Erdös, Random Matrices: Theory and Application 9 (2020).","chicago":"Cipolloni, Giorgio, and László Erdös. “Fluctuations for Differences of Linear Eigenvalue Statistics for Sample Covariance Matrices.” <i>Random Matrices: Theory and Application</i>. World Scientific Publishing, 2020. <a href=\"https://doi.org/10.1142/S2010326320500069\">https://doi.org/10.1142/S2010326320500069</a>.","ama":"Cipolloni G, Erdös L. Fluctuations for differences of linear eigenvalue statistics for sample covariance matrices. <i>Random Matrices: Theory and Application</i>. 2020;9(3). doi:<a href=\"https://doi.org/10.1142/S2010326320500069\">10.1142/S2010326320500069</a>","ista":"Cipolloni G, Erdös L. 2020. Fluctuations for differences of linear eigenvalue statistics for sample covariance matrices. Random Matrices: Theory and Application. 9(3), 2050006.","apa":"Cipolloni, G., &#38; Erdös, L. (2020). Fluctuations for differences of linear eigenvalue statistics for sample covariance matrices. <i>Random Matrices: Theory and Application</i>. World Scientific Publishing. <a href=\"https://doi.org/10.1142/S2010326320500069\">https://doi.org/10.1142/S2010326320500069</a>","mla":"Cipolloni, Giorgio, and László Erdös. “Fluctuations for Differences of Linear Eigenvalue Statistics for Sample Covariance Matrices.” <i>Random Matrices: Theory and Application</i>, vol. 9, no. 3, 2050006, World Scientific Publishing, 2020, doi:<a href=\"https://doi.org/10.1142/S2010326320500069\">10.1142/S2010326320500069</a>.","ieee":"G. Cipolloni and L. Erdös, “Fluctuations for differences of linear eigenvalue statistics for sample covariance matrices,” <i>Random Matrices: Theory and Application</i>, vol. 9, no. 3. World Scientific Publishing, 2020."},"doi":"10.1142/S2010326320500069","project":[{"grant_number":"338804","name":"Random matrices, universality and disordered quantum systems","_id":"258DCDE6-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"},{"call_identifier":"H2020","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","name":"International IST Doctoral Program","grant_number":"665385"}],"author":[{"orcid":"0000-0002-4901-7992","last_name":"Cipolloni","first_name":"Giorgio","id":"42198EFA-F248-11E8-B48F-1D18A9856A87","full_name":"Cipolloni, Giorgio"},{"full_name":"Erdös, László","id":"4DBD5372-F248-11E8-B48F-1D18A9856A87","first_name":"László","last_name":"Erdös","orcid":"0000-0001-5366-9603"}],"title":"Fluctuations for differences of linear eigenvalue statistics for sample covariance matrices","date_updated":"2025-07-10T11:53:26Z","arxiv":1,"day":"01","article_type":"original","publication_identifier":{"eissn":["2010-3271"],"issn":["2010-3263"]},"external_id":{"isi":["000547464400001"],"arxiv":["1806.08751"]},"issue":"3","status":"public","month":"07","publication":"Random Matrices: Theory and Application","publisher":"World Scientific Publishing","date_created":"2019-05-26T21:59:14Z","abstract":[{"text":"We prove a central limit theorem for the difference of linear eigenvalue statistics of a sample covariance matrix W˜ and its minor W. We find that the fluctuation of this difference is much smaller than those of the individual linear statistics, as a consequence of the strong correlation between the eigenvalues of W˜ and W. Our result identifies the fluctuation of the spatial derivative of the approximate Gaussian field in the recent paper by Dumitru and Paquette. Unlike in a similar result for Wigner matrices, for sample covariance matrices, the fluctuation may entirely vanish.","lang":"eng"}],"intvolume":"         9","language":[{"iso":"eng"}],"publication_status":"published","article_processing_charge":"No","year":"2020","date_published":"2020-07-01T00:00:00Z","article_number":"2050006","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"ec_funded":1,"type":"journal_article","isi":1},{"month":"04","status":"public","publication":"Foundations of Computational Mathematics","date_created":"2019-06-16T21:59:14Z","abstract":[{"text":"This paper presents two algorithms. The first decides the existence of a pointed homotopy between given simplicial maps 𝑓,𝑔:𝑋→𝑌, and the second computes the group [𝛴𝑋,𝑌]∗ of pointed homotopy classes of maps from a suspension; in both cases, the target Y is assumed simply connected. More generally, these algorithms work relative to 𝐴⊆𝑋.","lang":"eng"}],"publisher":"Springer Nature","language":[{"iso":"eng"}],"intvolume":"        20","publication_status":"published","year":"2020","article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2020-04-01T00:00:00Z","page":"311-330","type":"journal_article","isi":1,"oa":1,"_id":"6563","quality_controlled":"1","oa_version":"Preprint","main_file_link":[{"url":"https://arxiv.org/abs/1312.2337","open_access":"1"}],"department":[{"_id":"UlWa"}],"scopus_import":"1","volume":20,"project":[{"call_identifier":"FWF","_id":"26611F5C-B435-11E9-9278-68D0E5697425","name":"Algorithms for Embeddings and Homotopy Theory","grant_number":"P31312"}],"citation":{"short":"M. Filakovský, L. Vokřínek, Foundations of Computational Mathematics 20 (2020) 311–330.","chicago":"Filakovský, Marek, and Lukas Vokřínek. “Are Two given Maps Homotopic? An Algorithmic Viewpoint.” <i>Foundations of Computational Mathematics</i>. Springer Nature, 2020. <a href=\"https://doi.org/10.1007/s10208-019-09419-x\">https://doi.org/10.1007/s10208-019-09419-x</a>.","ista":"Filakovský M, Vokřínek L. 2020. Are two given maps homotopic? An algorithmic viewpoint. Foundations of Computational Mathematics. 20, 311–330.","ama":"Filakovský M, Vokřínek L. Are two given maps homotopic? An algorithmic viewpoint. <i>Foundations of Computational Mathematics</i>. 2020;20:311-330. doi:<a href=\"https://doi.org/10.1007/s10208-019-09419-x\">10.1007/s10208-019-09419-x</a>","apa":"Filakovský, M., &#38; Vokřínek, L. (2020). Are two given maps homotopic? An algorithmic viewpoint. <i>Foundations of Computational Mathematics</i>. Springer Nature. <a href=\"https://doi.org/10.1007/s10208-019-09419-x\">https://doi.org/10.1007/s10208-019-09419-x</a>","mla":"Filakovský, Marek, and Lukas Vokřínek. “Are Two given Maps Homotopic? An Algorithmic Viewpoint.” <i>Foundations of Computational Mathematics</i>, vol. 20, Springer Nature, 2020, pp. 311–30, doi:<a href=\"https://doi.org/10.1007/s10208-019-09419-x\">10.1007/s10208-019-09419-x</a>.","ieee":"M. Filakovský and L. Vokřínek, “Are two given maps homotopic? An algorithmic viewpoint,” <i>Foundations of Computational Mathematics</i>, vol. 20. Springer Nature, pp. 311–330, 2020."},"doi":"10.1007/s10208-019-09419-x","author":[{"id":"3E8AF77E-F248-11E8-B48F-1D18A9856A87","full_name":"Filakovský, Marek","first_name":"Marek","last_name":"Filakovský"},{"full_name":"Vokřínek, Lukas","last_name":"Vokřínek","first_name":"Lukas"}],"title":"Are two given maps homotopic? An algorithmic viewpoint","date_updated":"2025-07-10T11:53:32Z","day":"01","article_type":"original","publication_identifier":{"issn":["1615-3375"],"eissn":["1615-3383"]},"arxiv":1,"external_id":{"arxiv":["1312.2337"],"isi":["000522437400004"]}},{"_id":"6593","oa_version":"Submitted Version","quality_controlled":"1","project":[{"call_identifier":"FP7","_id":"25FBA906-B435-11E9-9278-68D0E5697425","name":"Discrete Optimization in Computer Vision: Theory and Practice","grant_number":"616160"}],"doi":"10.1007/s11075-019-00758-y","citation":{"ista":"Shehu Y, Li X-H, Dong Q-L. 2020. An efficient projection-type method for monotone variational inequalities in Hilbert spaces. Numerical Algorithms. 84, 365–388.","ama":"Shehu Y, Li X-H, Dong Q-L. An efficient projection-type method for monotone variational inequalities in Hilbert spaces. <i>Numerical Algorithms</i>. 2020;84:365-388. doi:<a href=\"https://doi.org/10.1007/s11075-019-00758-y\">10.1007/s11075-019-00758-y</a>","apa":"Shehu, Y., Li, X.-H., &#38; Dong, Q.-L. (2020). An efficient projection-type method for monotone variational inequalities in Hilbert spaces. <i>Numerical Algorithms</i>. Springer Nature. <a href=\"https://doi.org/10.1007/s11075-019-00758-y\">https://doi.org/10.1007/s11075-019-00758-y</a>","mla":"Shehu, Yekini, et al. “An Efficient Projection-Type Method for Monotone Variational Inequalities in Hilbert Spaces.” <i>Numerical Algorithms</i>, vol. 84, Springer Nature, 2020, pp. 365–88, doi:<a href=\"https://doi.org/10.1007/s11075-019-00758-y\">10.1007/s11075-019-00758-y</a>.","ieee":"Y. Shehu, X.-H. Li, and Q.-L. Dong, “An efficient projection-type method for monotone variational inequalities in Hilbert spaces,” <i>Numerical Algorithms</i>, vol. 84. Springer Nature, pp. 365–388, 2020.","short":"Y. Shehu, X.-H. Li, Q.-L. Dong, Numerical Algorithms 84 (2020) 365–388.","chicago":"Shehu, Yekini, Xiao-Huan Li, and Qiao-Li Dong. “An Efficient Projection-Type Method for Monotone Variational Inequalities in Hilbert Spaces.” <i>Numerical Algorithms</i>. Springer Nature, 2020. <a href=\"https://doi.org/10.1007/s11075-019-00758-y\">https://doi.org/10.1007/s11075-019-00758-y</a>."},"scopus_import":"1","department":[{"_id":"VlKo"}],"volume":84,"title":"An efficient projection-type method for monotone variational inequalities in Hilbert spaces","date_updated":"2024-11-04T13:52:40Z","author":[{"id":"3FC7CB58-F248-11E8-B48F-1D18A9856A87","full_name":"Shehu, Yekini","first_name":"Yekini","orcid":"0000-0001-9224-7139","last_name":"Shehu"},{"full_name":"Li, Xiao-Huan","first_name":"Xiao-Huan","last_name":"Li"},{"last_name":"Dong","first_name":"Qiao-Li","full_name":"Dong, Qiao-Li"}],"external_id":{"isi":["000528979000015"]},"day":"01","publication_identifier":{"issn":["1017-1398"],"eissn":["1572-9265"]},"article_type":"original","acknowledgement":"The research of this author is supported by the ERC grant at the IST.","file_date_updated":"2020-07-14T12:47:34Z","ddc":["000"],"publication":"Numerical Algorithms","corr_author":"1","status":"public","month":"05","language":[{"iso":"eng"}],"intvolume":"        84","abstract":[{"text":"We consider the monotone variational inequality problem in a Hilbert space and describe a projection-type method with inertial terms under the following properties: (a) The method generates a strongly convergent iteration sequence; (b) The method requires, at each iteration, only one projection onto the feasible set and two evaluations of the operator; (c) The method is designed for variational inequality for which the underline operator is monotone and uniformly continuous; (d) The method includes an inertial term. The latter is also shown to speed up the convergence in our numerical results. A comparison with some related methods is given and indicates that the new method is promising.","lang":"eng"}],"date_created":"2019-06-27T20:09:33Z","has_accepted_license":"1","publisher":"Springer Nature","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","date_published":"2020-05-01T00:00:00Z","publication_status":"published","article_processing_charge":"No","year":"2020","file":[{"creator":"kschuh","file_name":"ExtragradientMethodPaper.pdf","checksum":"bb1a1eb3ebb2df380863d0db594673ba","relation":"main_file","date_created":"2019-10-01T13:14:10Z","content_type":"application/pdf","access_level":"open_access","file_size":359654,"file_id":"6927","date_updated":"2020-07-14T12:47:34Z"}],"isi":1,"type":"journal_article","ec_funded":1,"oa":1,"page":"365-388"},{"oa":1,"type":"journal_article","ec_funded":1,"isi":1,"page":"2097–2150","date_published":"2020-03-01T00:00:00Z","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","file":[{"file_id":"6668","date_updated":"2020-07-14T12:47:35Z","date_created":"2019-07-24T07:19:10Z","relation":"main_file","checksum":"f9dd6dd615a698f1d3636c4a092fed23","creator":"dernst","file_name":"2019_CommMathPhysics_Benedikter.pdf","file_size":853289,"access_level":"open_access","content_type":"application/pdf"}],"publication_status":"published","year":"2020","article_processing_charge":"No","intvolume":"       374","language":[{"iso":"eng"}],"publisher":"Springer Nature","date_created":"2019-07-18T13:30:04Z","has_accepted_license":"1","abstract":[{"text":"While Hartree–Fock theory is well established as a fundamental approximation for interacting fermions, it has been unclear how to describe corrections to it due to many-body correlations. In this paper we start from the Hartree–Fock state given by plane waves and introduce collective particle–hole pair excitations. These pairs can be approximately described by a bosonic quadratic Hamiltonian. We use Bogoliubov theory to construct a trial state yielding a rigorous Gell-Mann–Brueckner–type upper bound to the ground state energy. Our result justifies the random-phase approximation in the mean-field scaling regime, for repulsive, regular interaction potentials.\r\n","lang":"eng"}],"publication":"Communications in Mathematical Physics","month":"03","ddc":["530"],"corr_author":"1","status":"public","external_id":{"isi":["000527910700019"],"arxiv":["1809.01902"]},"arxiv":1,"day":"01","publication_identifier":{"issn":["0010-3616"],"eissn":["1432-0916"]},"article_type":"original","file_date_updated":"2020-07-14T12:47:35Z","title":"Optimal upper bound for the correlation energy of a Fermi gas in the mean-field regime","date_updated":"2025-04-14T07:27:00Z","author":[{"orcid":"0000-0002-1071-6091","last_name":"Benedikter","first_name":"Niels P","id":"3DE6C32A-F248-11E8-B48F-1D18A9856A87","full_name":"Benedikter, Niels P"},{"full_name":"Nam, Phan Thành","last_name":"Nam","first_name":"Phan Thành"},{"last_name":"Porta","first_name":"Marcello","full_name":"Porta, Marcello"},{"full_name":"Schlein, Benjamin","last_name":"Schlein","first_name":"Benjamin"},{"last_name":"Seiringer","orcid":"0000-0002-6781-0521","first_name":"Robert","full_name":"Seiringer, Robert","id":"4AFD0470-F248-11E8-B48F-1D18A9856A87"}],"tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"citation":{"chicago":"Benedikter, Niels P, Phan Thành Nam, Marcello Porta, Benjamin Schlein, and Robert Seiringer. “Optimal Upper Bound for the Correlation Energy of a Fermi Gas in the Mean-Field Regime.” <i>Communications in Mathematical Physics</i>. Springer Nature, 2020. <a href=\"https://doi.org/10.1007/s00220-019-03505-5\">https://doi.org/10.1007/s00220-019-03505-5</a>.","short":"N.P. Benedikter, P.T. Nam, M. Porta, B. Schlein, R. Seiringer, Communications in Mathematical Physics 374 (2020) 2097–2150.","ieee":"N. P. Benedikter, P. T. Nam, M. Porta, B. Schlein, and R. Seiringer, “Optimal upper bound for the correlation energy of a Fermi gas in the mean-field regime,” <i>Communications in Mathematical Physics</i>, vol. 374. Springer Nature, pp. 2097–2150, 2020.","mla":"Benedikter, Niels P., et al. “Optimal Upper Bound for the Correlation Energy of a Fermi Gas in the Mean-Field Regime.” <i>Communications in Mathematical Physics</i>, vol. 374, Springer Nature, 2020, pp. 2097–2150, doi:<a href=\"https://doi.org/10.1007/s00220-019-03505-5\">10.1007/s00220-019-03505-5</a>.","apa":"Benedikter, N. P., Nam, P. T., Porta, M., Schlein, B., &#38; Seiringer, R. (2020). Optimal upper bound for the correlation energy of a Fermi gas in the mean-field regime. <i>Communications in Mathematical Physics</i>. Springer Nature. <a href=\"https://doi.org/10.1007/s00220-019-03505-5\">https://doi.org/10.1007/s00220-019-03505-5</a>","ista":"Benedikter NP, Nam PT, Porta M, Schlein B, Seiringer R. 2020. Optimal upper bound for the correlation energy of a Fermi gas in the mean-field regime. Communications in Mathematical Physics. 374, 2097–2150.","ama":"Benedikter NP, Nam PT, Porta M, Schlein B, Seiringer R. Optimal upper bound for the correlation energy of a Fermi gas in the mean-field regime. <i>Communications in Mathematical Physics</i>. 2020;374:2097–2150. doi:<a href=\"https://doi.org/10.1007/s00220-019-03505-5\">10.1007/s00220-019-03505-5</a>"},"doi":"10.1007/s00220-019-03505-5","project":[{"_id":"3AC91DDA-15DF-11EA-824D-93A3E7B544D1","call_identifier":"FWF","name":"FWF Open Access Fund"},{"name":"Structure of the Excitation Spectrum for Many-Body Quantum Systems","grant_number":"P27533_N27","call_identifier":"FWF","_id":"25C878CE-B435-11E9-9278-68D0E5697425"},{"grant_number":"694227","name":"Analysis of quantum many-body systems","_id":"25C6DC12-B435-11E9-9278-68D0E5697425","call_identifier":"H2020"}],"volume":374,"scopus_import":"1","department":[{"_id":"RoSe"}],"oa_version":"Published Version","quality_controlled":"1","_id":"6649"},{"month":"12","status":"public","publication":"Annals of Statistics","issue":"6","language":[{"iso":"eng"}],"intvolume":"        48","date_created":"2019-07-31T09:39:42Z","abstract":[{"text":"Fitting a function by using linear combinations of a large number N of `simple' components is one of the most fruitful ideas in statistical learning. This idea lies at the core of a variety of methods, from two-layer neural networks to kernel regression, to boosting. In general, the resulting risk minimization problem is non-convex and is solved by gradient descent or its variants. Unfortunately, little is known about global convergence properties of these approaches.\r\nHere we consider the problem of learning a concave function f on a compact convex domain Ω⊆ℝd, using linear combinations of `bump-like' components (neurons). The parameters to be fitted are the centers of N bumps, and the resulting empirical risk minimization problem is highly non-convex. We prove that, in the limit in which the number of neurons diverges, the evolution of gradient descent converges to a Wasserstein gradient flow in the space of probability distributions over Ω. Further, when the bump width δ tends to 0, this gradient flow has a limit which is a viscous porous medium equation. Remarkably, the cost function optimized by this gradient flow exhibits a special property known as displacement convexity, which implies exponential convergence rates for N→∞, δ→0. Surprisingly, this asymptotic theory appears to capture well the behavior for moderate values of δ,N. Explaining this phenomenon, and understanding the dependence on δ,N in a quantitative manner remains an outstanding challenge.","lang":"eng"}],"publisher":"Institute of Mathematical Statistics","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2020-12-11T00:00:00Z","publication_status":"published","year":"2020","article_processing_charge":"No","type":"journal_article","isi":1,"oa":1,"page":"3619-3642","_id":"6748","oa_version":"Preprint","quality_controlled":"1","main_file_link":[{"url":"https://arxiv.org/abs/1901.01375","open_access":"1"}],"doi":"10.1214/20-AOS1945","citation":{"ieee":"A. Javanmard, M. Mondelli, and A. Montanari, “Analysis of a two-layer neural network via displacement convexity,” <i>Annals of Statistics</i>, vol. 48, no. 6. Institute of Mathematical Statistics, pp. 3619–3642, 2020.","mla":"Javanmard, Adel, et al. “Analysis of a Two-Layer Neural Network via Displacement Convexity.” <i>Annals of Statistics</i>, vol. 48, no. 6, Institute of Mathematical Statistics, 2020, pp. 3619–42, doi:<a href=\"https://doi.org/10.1214/20-AOS1945\">10.1214/20-AOS1945</a>.","apa":"Javanmard, A., Mondelli, M., &#38; Montanari, A. (2020). Analysis of a two-layer neural network via displacement convexity. <i>Annals of Statistics</i>. Institute of Mathematical Statistics. <a href=\"https://doi.org/10.1214/20-AOS1945\">https://doi.org/10.1214/20-AOS1945</a>","ama":"Javanmard A, Mondelli M, Montanari A. Analysis of a two-layer neural network via displacement convexity. <i>Annals of Statistics</i>. 2020;48(6):3619-3642. doi:<a href=\"https://doi.org/10.1214/20-AOS1945\">10.1214/20-AOS1945</a>","ista":"Javanmard A, Mondelli M, Montanari A. 2020. Analysis of a two-layer neural network via displacement convexity. Annals of Statistics. 48(6), 3619–3642.","chicago":"Javanmard, Adel, Marco Mondelli, and Andrea Montanari. “Analysis of a Two-Layer Neural Network via Displacement Convexity.” <i>Annals of Statistics</i>. Institute of Mathematical Statistics, 2020. <a href=\"https://doi.org/10.1214/20-AOS1945\">https://doi.org/10.1214/20-AOS1945</a>.","short":"A. Javanmard, M. Mondelli, A. Montanari, Annals of Statistics 48 (2020) 3619–3642."},"department":[{"_id":"MaMo"}],"scopus_import":"1","volume":48,"title":"Analysis of a two-layer neural network via displacement convexity","date_updated":"2024-10-21T06:02:33Z","author":[{"full_name":"Javanmard, Adel","last_name":"Javanmard","first_name":"Adel"},{"id":"27EB676C-8706-11E9-9510-7717E6697425","full_name":"Mondelli, Marco","orcid":"0000-0002-3242-7020","last_name":"Mondelli","first_name":"Marco"},{"last_name":"Montanari","first_name":"Andrea","full_name":"Montanari, Andrea"}],"external_id":{"isi":["000598369200021"],"arxiv":["1901.01375"]},"day":"11","publication_identifier":{"issn":["1932-6157"],"eissn":["1941-7330"]},"article_type":"original","arxiv":1},{"page":"42-55","oa":1,"type":"journal_article","isi":1,"file":[{"date_updated":"2020-10-09T06:31:22Z","success":1,"file_id":"8639","file_size":1413001,"content_type":"application/pdf","access_level":"open_access","relation":"main_file","date_created":"2020-10-09T06:31:22Z","checksum":"e86635417f45eb2cd75778f91382f737","file_name":"2020_TheoreticalCS_Avni.pdf","creator":"dernst"}],"publication_status":"published","article_processing_charge":"No","year":"2020","date_published":"2020-02-06T00:00:00Z","user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","publisher":"Elsevier","date_created":"2019-08-04T21:59:20Z","abstract":[{"lang":"eng","text":"In resource allocation games, selfish players share resources that are needed in order to fulfill their objectives. The cost of using a resource depends on the load on it. In the traditional setting, the players make their choices concurrently and in one-shot. That is, a strategy for a player is a subset of the resources. We introduce and study dynamic resource allocation games. In this setting, the game proceeds in phases. In each phase each player chooses one resource. A scheduler dictates the order in which the players proceed in a phase, possibly scheduling several players to proceed concurrently. The game ends when each player has collected a set of resources that fulfills his objective. The cost for each player then depends on this set as well as on the load on the resources in it – we consider both congestion and cost-sharing games. We argue that the dynamic setting is the suitable setting for many applications in practice. We study the stability of dynamic resource allocation games, where the appropriate notion of stability is that of subgame perfect equilibrium, study the inefficiency incurred due to selfish behavior, and also study problems that are particular to the dynamic setting, like constraints on the order in which resources can be chosen or the problem of finding a scheduler that achieves stability."}],"has_accepted_license":"1","intvolume":"       807","language":[{"iso":"eng"}],"month":"02","publication":"Theoretical Computer Science","ddc":["000"],"status":"public","day":"06","file_date_updated":"2020-10-09T06:31:22Z","related_material":{"record":[{"id":"1341","relation":"earlier_version","status":"public"}]},"article_type":"original","publication_identifier":{"issn":["0304-3975"]},"external_id":{"isi":["000512219400004"]},"author":[{"first_name":"Guy","orcid":"0000-0001-5588-8287","last_name":"Avni","id":"463C8BC2-F248-11E8-B48F-1D18A9856A87","full_name":"Avni, Guy"},{"orcid":"0000−0002−2985−7724","last_name":"Henzinger","first_name":"Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","full_name":"Henzinger, Thomas A"},{"full_name":"Kupferman, Orna","last_name":"Kupferman","first_name":"Orna"}],"title":"Dynamic resource allocation games","date_updated":"2026-04-16T09:35:15Z","volume":807,"scopus_import":"1","department":[{"_id":"ToHe"}],"citation":{"ieee":"G. Avni, T. A. Henzinger, and O. Kupferman, “Dynamic resource allocation games,” <i>Theoretical Computer Science</i>, vol. 807. Elsevier, pp. 42–55, 2020.","mla":"Avni, Guy, et al. “Dynamic Resource Allocation Games.” <i>Theoretical Computer Science</i>, vol. 807, Elsevier, 2020, pp. 42–55, doi:<a href=\"https://doi.org/10.1016/j.tcs.2019.06.031\">10.1016/j.tcs.2019.06.031</a>.","ama":"Avni G, Henzinger TA, Kupferman O. Dynamic resource allocation games. <i>Theoretical Computer Science</i>. 2020;807:42-55. doi:<a href=\"https://doi.org/10.1016/j.tcs.2019.06.031\">10.1016/j.tcs.2019.06.031</a>","ista":"Avni G, Henzinger TA, Kupferman O. 2020. Dynamic resource allocation games. Theoretical Computer Science. 807, 42–55.","apa":"Avni, G., Henzinger, T. A., &#38; Kupferman, O. (2020). Dynamic resource allocation games. <i>Theoretical Computer Science</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.tcs.2019.06.031\">https://doi.org/10.1016/j.tcs.2019.06.031</a>","chicago":"Avni, Guy, Thomas A Henzinger, and Orna Kupferman. “Dynamic Resource Allocation Games.” <i>Theoretical Computer Science</i>. Elsevier, 2020. <a href=\"https://doi.org/10.1016/j.tcs.2019.06.031\">https://doi.org/10.1016/j.tcs.2019.06.031</a>.","short":"G. Avni, T.A. Henzinger, O. Kupferman, Theoretical Computer Science 807 (2020) 42–55."},"doi":"10.1016/j.tcs.2019.06.031","project":[{"name":"Rigorous Systems Engineering","grant_number":"S11402-N23","call_identifier":"FWF","_id":"25F2ACDE-B435-11E9-9278-68D0E5697425"},{"grant_number":"Z211","name":"Formal methods for the design and analysis of complex systems","_id":"25F42A32-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"},{"call_identifier":"FWF","_id":"264B3912-B435-11E9-9278-68D0E5697425","name":"Formal Methods meets Algorithmic Game Theory","grant_number":"M02369"}],"oa_version":"Submitted Version","quality_controlled":"1","_id":"6761"},{"author":[{"full_name":"Stella, Federico","id":"39AF1E74-F248-11E8-B48F-1D18A9856A87","first_name":"Federico","last_name":"Stella","orcid":"0000-0001-9439-3148"},{"last_name":"Urdapilleta","first_name":"Eugenio","full_name":"Urdapilleta, Eugenio"},{"full_name":"Luo, Yifan","first_name":"Yifan","last_name":"Luo"},{"last_name":"Treves","first_name":"Alessandro","full_name":"Treves, Alessandro"}],"title":"Partial coherence and frustration in self-organizing spherical grids","date_updated":"2025-05-22T11:13:25Z","day":"01","file_date_updated":"2020-07-14T12:47:40Z","publication_identifier":{"eissn":["1098-1063"],"issn":["1050-9631"]},"article_type":"original","external_id":{"pmid":["31339190"],"isi":["000477299600001"]},"oa_version":"Published Version","quality_controlled":"1","_id":"6796","volume":30,"scopus_import":"1","department":[{"_id":"JoCs"}],"doi":"10.1002/hipo.23144","tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"citation":{"short":"F. Stella, E. Urdapilleta, Y. Luo, A. Treves, Hippocampus 30 (2020) 302–313.","chicago":"Stella, Federico, Eugenio Urdapilleta, Yifan Luo, and Alessandro Treves. “Partial Coherence and Frustration in Self-Organizing Spherical Grids.” <i>Hippocampus</i>. Wiley, 2020. <a href=\"https://doi.org/10.1002/hipo.23144\">https://doi.org/10.1002/hipo.23144</a>.","ama":"Stella F, Urdapilleta E, Luo Y, Treves A. Partial coherence and frustration in self-organizing spherical grids. <i>Hippocampus</i>. 2020;30(4):302-313. doi:<a href=\"https://doi.org/10.1002/hipo.23144\">10.1002/hipo.23144</a>","apa":"Stella, F., Urdapilleta, E., Luo, Y., &#38; Treves, A. (2020). Partial coherence and frustration in self-organizing spherical grids. <i>Hippocampus</i>. Wiley. <a href=\"https://doi.org/10.1002/hipo.23144\">https://doi.org/10.1002/hipo.23144</a>","ista":"Stella F, Urdapilleta E, Luo Y, Treves A. 2020. Partial coherence and frustration in self-organizing spherical grids. Hippocampus. 30(4), 302–313.","mla":"Stella, Federico, et al. “Partial Coherence and Frustration in Self-Organizing Spherical Grids.” <i>Hippocampus</i>, vol. 30, no. 4, Wiley, 2020, pp. 302–13, doi:<a href=\"https://doi.org/10.1002/hipo.23144\">10.1002/hipo.23144</a>.","ieee":"F. Stella, E. Urdapilleta, Y. Luo, and A. Treves, “Partial coherence and frustration in self-organizing spherical grids,” <i>Hippocampus</i>, vol. 30, no. 4. Wiley, pp. 302–313, 2020."},"file":[{"content_type":"application/pdf","access_level":"open_access","file_size":2370658,"checksum":"7b54d22bfbfc0d1188a9ea24d985bfb2","creator":"dernst","file_name":"2019_Hippocampus_Stella.pdf","relation":"main_file","date_created":"2019-08-12T07:53:33Z","date_updated":"2020-07-14T12:47:40Z","file_id":"6800"}],"publication_status":"published","year":"2020","article_processing_charge":"No","date_published":"2020-04-01T00:00:00Z","user_id":"9947682f-b9fa-11ee-9c4a-b3ffaafe6614","page":"302-313","oa":1,"type":"journal_article","isi":1,"issue":"4","month":"04","status":"public","ddc":["570"],"publication":"Hippocampus","publisher":"Wiley","abstract":[{"lang":"eng","text":"Nearby grid cells have been observed to express a remarkable degree of long-rangeorder, which is often idealized as extending potentially to infinity. Yet their strict peri-odic firing and ensemble coherence are theoretically possible only in flat environments, much unlike the burrows which rodents usually live in. Are the symmetrical, coherent grid maps inferred in the lab relevant to chart their way in their natural habitat? We consider spheres as simple models of curved environments and waiting for the appropriate experiments to be performed, we use our adaptation model to predict what grid maps would emerge in a network with the same type of recurrent connections, which on the plane produce coherence among the units. We find that on the sphere such connections distort the maps that single grid units would express on their own, and aggregate them into clusters. When remapping to a different spherical environment, units in each cluster maintain only partial coherence, similar to what is observed in disordered materials, such as spin glasses."}],"has_accepted_license":"1","date_created":"2019-08-11T21:59:24Z","pmid":1,"intvolume":"        30","language":[{"iso":"eng"}]},{"external_id":{"isi":["000525860400005"],"pmid":["31344404"]},"publication_identifier":{"issn":["1046-2023"]},"article_type":"original","day":"01","date_updated":"2025-04-14T09:39:25Z","title":"Strategies to maximize performance in STimulated Emission Depletion (STED) nanoscopy of biological specimens","author":[{"full_name":"Jahr, Wiebke","id":"425C1CE8-F248-11E8-B48F-1D18A9856A87","last_name":"Jahr","first_name":"Wiebke"},{"full_name":"Velicky, Philipp","id":"39BDC62C-F248-11E8-B48F-1D18A9856A87","first_name":"Philipp","last_name":"Velicky","orcid":"0000-0002-2340-7431"},{"full_name":"Danzl, Johann G","id":"42EFD3B6-F248-11E8-B48F-1D18A9856A87","last_name":"Danzl","orcid":"0000-0001-8559-3973","first_name":"Johann G"}],"project":[{"call_identifier":"FWF","_id":"265CB4D0-B435-11E9-9278-68D0E5697425","name":"Optical control of synaptic function via adhesion molecules","grant_number":"I03600"},{"name":"High-speed 3D-nanoscopy to study the role of adhesion during 3D cell migration","grant_number":"LT00057","_id":"2668BFA0-B435-11E9-9278-68D0E5697425"}],"doi":"10.1016/j.ymeth.2019.07.019","citation":{"chicago":"Jahr, Wiebke, Philipp Velicky, and Johann G Danzl. “Strategies to Maximize Performance in STimulated Emission Depletion (STED) Nanoscopy of Biological Specimens.” <i>Methods</i>. Elsevier, 2020. <a href=\"https://doi.org/10.1016/j.ymeth.2019.07.019\">https://doi.org/10.1016/j.ymeth.2019.07.019</a>.","short":"W. Jahr, P. Velicky, J.G. Danzl, Methods 174 (2020) 27–41.","ieee":"W. Jahr, P. Velicky, and J. G. Danzl, “Strategies to maximize performance in STimulated Emission Depletion (STED) nanoscopy of biological specimens,” <i>Methods</i>, vol. 174, no. 3. Elsevier, pp. 27–41, 2020.","mla":"Jahr, Wiebke, et al. “Strategies to Maximize Performance in STimulated Emission Depletion (STED) Nanoscopy of Biological Specimens.” <i>Methods</i>, vol. 174, no. 3, Elsevier, 2020, pp. 27–41, doi:<a href=\"https://doi.org/10.1016/j.ymeth.2019.07.019\">10.1016/j.ymeth.2019.07.019</a>.","apa":"Jahr, W., Velicky, P., &#38; Danzl, J. G. (2020). Strategies to maximize performance in STimulated Emission Depletion (STED) nanoscopy of biological specimens. <i>Methods</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.ymeth.2019.07.019\">https://doi.org/10.1016/j.ymeth.2019.07.019</a>","ista":"Jahr W, Velicky P, Danzl JG. 2020. Strategies to maximize performance in STimulated Emission Depletion (STED) nanoscopy of biological specimens. Methods. 174(3), 27–41.","ama":"Jahr W, Velicky P, Danzl JG. Strategies to maximize performance in STimulated Emission Depletion (STED) nanoscopy of biological specimens. <i>Methods</i>. 2020;174(3):27-41. doi:<a href=\"https://doi.org/10.1016/j.ymeth.2019.07.019\">10.1016/j.ymeth.2019.07.019</a>"},"department":[{"_id":"JoDa"}],"scopus_import":"1","volume":174,"_id":"6808","main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7100895/","open_access":"1"}],"quality_controlled":"1","oa_version":"Submitted Version","type":"journal_article","isi":1,"oa":1,"page":"27-41","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","date_published":"2020-03-01T00:00:00Z","article_processing_charge":"No","year":"2020","publication_status":"published","language":[{"iso":"eng"}],"intvolume":"       174","abstract":[{"lang":"eng","text":"Super-resolution fluorescence microscopy has become an important catalyst for discovery in the life sciences. In STimulated Emission Depletion (STED) microscopy, a pattern of light drives fluorophores from a signal-emitting on-state to a non-signalling off-state. Only emitters residing in a sub-diffraction volume around an intensity minimum are allowed to fluoresce, rendering them distinguishable from the nearby, but dark fluorophores. STED routinely achieves resolution in the few tens of nanometers range in biological samples and is suitable for live imaging. Here, we review the working principle of STED and provide general guidelines for successful STED imaging. The strive for ever higher resolution comes at the cost of increased light burden. We discuss techniques to reduce light exposure and mitigate its detrimental effects on the specimen. These include specialized illumination strategies as well as protecting fluorophores from photobleaching mediated by high-intensity STED light. This opens up the prospect of volumetric imaging in living cells and tissues with diffraction-unlimited resolution in all three spatial dimensions."}],"pmid":1,"date_created":"2019-08-12T16:36:32Z","publisher":"Elsevier","status":"public","month":"03","publication":"Methods","issue":"3"},{"page":"1311-1395","oa":1,"isi":1,"ec_funded":1,"type":"journal_article","year":"2020","article_processing_charge":"No","publication_status":"published","date_published":"2020-06-01T00:00:00Z","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","publisher":"Springer","date_created":"2019-09-24T17:30:59Z","abstract":[{"lang":"eng","text":"We consider systems of bosons trapped in a box, in the Gross–Pitaevskii regime. We show that low-energy states exhibit complete Bose–Einstein condensation with an optimal bound on the number of orthogonal excitations. This extends recent results obtained in Boccato et al. (Commun Math Phys 359(3):975–1026, 2018), removing the assumption of small interaction potential."}],"intvolume":"       376","language":[{"iso":"eng"}],"publication":"Communications in Mathematical Physics","status":"public","month":"06","arxiv":1,"acknowledgement":"We would like to thank P. T. Nam and R. Seiringer for several useful discussions and\r\nfor suggesting us to use the localization techniques from [9]. C. Boccato has received funding from the\r\nEuropean Research Council (ERC) under the programme Horizon 2020 (Grant Agreement 694227). B. Schlein gratefully acknowledges support from the NCCR SwissMAP and from the Swiss National Foundation of Science (Grant No. 200020_1726230) through the SNF Grant “Dynamical and energetic properties of Bose–Einstein condensates”.","publication_identifier":{"issn":["0010-3616"],"eissn":["1432-0916"]},"article_type":"original","day":"01","external_id":{"isi":["000536053300012"],"arxiv":["1812.03086"]},"author":[{"full_name":"Boccato, Chiara","id":"342E7E22-F248-11E8-B48F-1D18A9856A87","last_name":"Boccato","first_name":"Chiara"},{"full_name":"Brennecke, Christian","last_name":"Brennecke","first_name":"Christian"},{"first_name":"Serena","last_name":"Cenatiempo","full_name":"Cenatiempo, Serena"},{"full_name":"Schlein, Benjamin","last_name":"Schlein","first_name":"Benjamin"}],"date_updated":"2025-04-14T07:27:00Z","title":"Optimal rate for Bose-Einstein condensation in the Gross-Pitaevskii regime","volume":376,"scopus_import":"1","department":[{"_id":"RoSe"}],"doi":"10.1007/s00220-019-03555-9","citation":{"mla":"Boccato, Chiara, et al. “Optimal Rate for Bose-Einstein Condensation in the Gross-Pitaevskii Regime.” <i>Communications in Mathematical Physics</i>, vol. 376, Springer, 2020, pp. 1311–95, doi:<a href=\"https://doi.org/10.1007/s00220-019-03555-9\">10.1007/s00220-019-03555-9</a>.","ieee":"C. Boccato, C. Brennecke, S. Cenatiempo, and B. Schlein, “Optimal rate for Bose-Einstein condensation in the Gross-Pitaevskii regime,” <i>Communications in Mathematical Physics</i>, vol. 376. Springer, pp. 1311–1395, 2020.","apa":"Boccato, C., Brennecke, C., Cenatiempo, S., &#38; Schlein, B. (2020). Optimal rate for Bose-Einstein condensation in the Gross-Pitaevskii regime. <i>Communications in Mathematical Physics</i>. Springer. <a href=\"https://doi.org/10.1007/s00220-019-03555-9\">https://doi.org/10.1007/s00220-019-03555-9</a>","ista":"Boccato C, Brennecke C, Cenatiempo S, Schlein B. 2020. Optimal rate for Bose-Einstein condensation in the Gross-Pitaevskii regime. Communications in Mathematical Physics. 376, 1311–1395.","ama":"Boccato C, Brennecke C, Cenatiempo S, Schlein B. Optimal rate for Bose-Einstein condensation in the Gross-Pitaevskii regime. <i>Communications in Mathematical Physics</i>. 2020;376:1311-1395. doi:<a href=\"https://doi.org/10.1007/s00220-019-03555-9\">10.1007/s00220-019-03555-9</a>","chicago":"Boccato, Chiara, Christian Brennecke, Serena Cenatiempo, and Benjamin Schlein. “Optimal Rate for Bose-Einstein Condensation in the Gross-Pitaevskii Regime.” <i>Communications in Mathematical Physics</i>. Springer, 2020. <a href=\"https://doi.org/10.1007/s00220-019-03555-9\">https://doi.org/10.1007/s00220-019-03555-9</a>.","short":"C. Boccato, C. Brennecke, S. Cenatiempo, B. Schlein, Communications in Mathematical Physics 376 (2020) 1311–1395."},"project":[{"_id":"25C6DC12-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","grant_number":"694227","name":"Analysis of quantum many-body systems"}],"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1812.03086"}],"oa_version":"Preprint","quality_controlled":"1","_id":"6906"},{"date_published":"2020-04-01T00:00:00Z","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","file":[{"creator":"dernst","checksum":"155e63edf664dcacb3bdc1c2223e606f","file_name":"2019_IJCV_Sun.pdf","date_created":"2019-11-26T10:30:02Z","relation":"main_file","access_level":"open_access","content_type":"application/pdf","file_size":1715072,"file_id":"7110","date_updated":"2020-07-14T12:47:45Z"}],"publication_status":"published","year":"2020","article_processing_charge":"Yes (via OA deal)","oa":1,"isi":1,"ec_funded":1,"type":"journal_article","page":"970-995","ddc":["004"],"status":"public","month":"04","corr_author":"1","publication":"International Journal of Computer Vision","issue":"4","intvolume":"       128","language":[{"iso":"eng"}],"publisher":"Springer Nature","has_accepted_license":"1","date_created":"2019-10-14T09:14:28Z","abstract":[{"lang":"eng","text":"We study the problem of automatically detecting if a given multi-class classifier operates outside of its specifications (out-of-specs), i.e. on input data from a different distribution than what it was trained for. This is an important problem to solve on the road towards creating reliable computer vision systems for real-world applications, because the quality of a classifier’s predictions cannot be guaranteed if it operates out-of-specs. Previously proposed methods for out-of-specs detection make decisions on the level of single inputs. This, however, is insufficient to achieve low false positive rate and high false negative rates at the same time. In this work, we describe a new procedure named KS(conf), based on statistical reasoning. Its main component is a classical Kolmogorov–Smirnov test that is applied to the set of predicted confidence values for batches of samples. Working with batches instead of single samples allows increasing the true positive rate without negatively affecting the false positive rate, thereby overcoming a crucial limitation of single sample tests. We show by extensive experiments using a variety of convolutional network architectures and datasets that KS(conf) reliably detects out-of-specs situations even under conditions where other tests fail. It furthermore has a number of properties that make it an excellent candidate for practical deployment: it is easy to implement, adds almost no overhead to the system, works with any classifier that outputs confidence scores, and requires no a priori knowledge about how the data distribution could change."}],"title":"KS(conf): A light-weight test if a multiclass classifier operates outside of its specifications","date_updated":"2025-04-15T07:10:25Z","author":[{"last_name":"Sun","first_name":"Rémy","full_name":"Sun, Rémy"},{"id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","full_name":"Lampert, Christoph","orcid":"0000-0001-8622-7887","last_name":"Lampert","first_name":"Christoph"}],"external_id":{"isi":["000494406800001"]},"day":"01","related_material":{"link":[{"url":"https://doi.org/10.1007/s11263-019-01262-5","relation":"erratum"}],"record":[{"id":"6482","relation":"earlier_version","status":"public"}]},"publication_identifier":{"issn":["0920-5691"],"eissn":["1573-1405"]},"article_type":"original","file_date_updated":"2020-07-14T12:47:45Z","quality_controlled":"1","oa_version":"Published Version","_id":"6944","doi":"10.1007/s11263-019-01232-x","tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"citation":{"mla":"Sun, Rémy, and Christoph Lampert. “KS(Conf): A Light-Weight Test If a Multiclass Classifier Operates Outside of Its Specifications.” <i>International Journal of Computer Vision</i>, vol. 128, no. 4, Springer Nature, 2020, pp. 970–95, doi:<a href=\"https://doi.org/10.1007/s11263-019-01232-x\">10.1007/s11263-019-01232-x</a>.","ieee":"R. Sun and C. Lampert, “KS(conf): A light-weight test if a multiclass classifier operates outside of its specifications,” <i>International Journal of Computer Vision</i>, vol. 128, no. 4. Springer Nature, pp. 970–995, 2020.","ista":"Sun R, Lampert C. 2020. KS(conf): A light-weight test if a multiclass classifier operates outside of its specifications. International Journal of Computer Vision. 128(4), 970–995.","apa":"Sun, R., &#38; Lampert, C. (2020). KS(conf): A light-weight test if a multiclass classifier operates outside of its specifications. <i>International Journal of Computer Vision</i>. Springer Nature. <a href=\"https://doi.org/10.1007/s11263-019-01232-x\">https://doi.org/10.1007/s11263-019-01232-x</a>","ama":"Sun R, Lampert C. KS(conf): A light-weight test if a multiclass classifier operates outside of its specifications. <i>International Journal of Computer Vision</i>. 2020;128(4):970-995. doi:<a href=\"https://doi.org/10.1007/s11263-019-01232-x\">10.1007/s11263-019-01232-x</a>","chicago":"Sun, Rémy, and Christoph Lampert. “KS(Conf): A Light-Weight Test If a Multiclass Classifier Operates Outside of Its Specifications.” <i>International Journal of Computer Vision</i>. Springer Nature, 2020. <a href=\"https://doi.org/10.1007/s11263-019-01232-x\">https://doi.org/10.1007/s11263-019-01232-x</a>.","short":"R. Sun, C. Lampert, International Journal of Computer Vision 128 (2020) 970–995."},"project":[{"name":"Lifelong Learning of Visual Scene Understanding","grant_number":"308036","call_identifier":"FP7","_id":"2532554C-B435-11E9-9278-68D0E5697425"},{"_id":"B67AFEDC-15C9-11EA-A837-991A96BB2854","name":"IST Austria Open Access Fund"}],"volume":128,"scopus_import":"1","department":[{"_id":"ChLa"}]},{"quality_controlled":"1","oa_version":"None","status":"public","publication":"Nature Physics","month":"01","extern":"1","_id":"6976","issue":"1","citation":{"ista":"Dieleman P, Vasmel N, Waitukaitis SR, van Hecke M. 2020. Jigsaw puzzle design of pluripotent origami. Nature Physics. 16(1), 63–68.","ama":"Dieleman P, Vasmel N, Waitukaitis SR, van Hecke M. Jigsaw puzzle design of pluripotent origami. <i>Nature Physics</i>. 2020;16(1):63–68. doi:<a href=\"https://doi.org/10.1038/s41567-019-0677-3\">10.1038/s41567-019-0677-3</a>","apa":"Dieleman, P., Vasmel, N., Waitukaitis, S. R., &#38; van Hecke, M. (2020). Jigsaw puzzle design of pluripotent origami. <i>Nature Physics</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41567-019-0677-3\">https://doi.org/10.1038/s41567-019-0677-3</a>","mla":"Dieleman, Peter, et al. “Jigsaw Puzzle Design of Pluripotent Origami.” <i>Nature Physics</i>, vol. 16, no. 1, Springer Nature, 2020, pp. 63–68, doi:<a href=\"https://doi.org/10.1038/s41567-019-0677-3\">10.1038/s41567-019-0677-3</a>.","ieee":"P. Dieleman, N. Vasmel, S. R. Waitukaitis, and M. van Hecke, “Jigsaw puzzle design of pluripotent origami,” <i>Nature Physics</i>, vol. 16, no. 1. Springer Nature, pp. 63–68, 2020.","short":"P. Dieleman, N. Vasmel, S.R. Waitukaitis, M. van Hecke, Nature Physics 16 (2020) 63–68.","chicago":"Dieleman, Peter, Niek Vasmel, Scott R Waitukaitis, and Martin van Hecke. “Jigsaw Puzzle Design of Pluripotent Origami.” <i>Nature Physics</i>. Springer Nature, 2020. <a href=\"https://doi.org/10.1038/s41567-019-0677-3\">https://doi.org/10.1038/s41567-019-0677-3</a>."},"intvolume":"        16","doi":"10.1038/s41567-019-0677-3","language":[{"iso":"eng"}],"publisher":"Springer Nature","volume":16,"abstract":[{"lang":"eng","text":"Origami is rapidly transforming the design of robots1,2, deployable structures3,4,5,6 and metamaterials7,8,9,10,11,12,13,14. However, as foldability requires a large number of complex compatibility conditions that are difficult to satisfy, the design of crease patterns is limited to heuristics and computer optimization. Here we introduce a systematic strategy that enables intuitive and effective design of complex crease patterns that are guaranteed to fold. First, we exploit symmetries to construct 140 distinct foldable motifs, and represent these as jigsaw puzzle pieces. We then show that when these pieces are fitted together they encode foldable crease patterns. This maps origami design to solving combinatorial problems, which allows us to systematically create, count and classify a vast number of crease patterns. We show that all of these crease patterns are pluripotent—capable of folding into multiple shapes—and solve exactly for the number of possible shapes for each pattern. Finally, we employ our framework to rationally design a crease pattern that folds into two independently defined target shapes, and fabricate such pluripotent origami. Our results provide physicists, mathematicians and engineers with a powerful new design strategy."}],"date_created":"2019-10-31T07:51:44Z","title":"Jigsaw puzzle design of pluripotent origami","date_published":"2020-01-01T00:00:00Z","date_updated":"2021-01-12T08:11:16Z","user_id":"D865714E-FA4E-11E9-B85B-F5C5E5697425","author":[{"last_name":"Dieleman","first_name":"Peter","full_name":"Dieleman, Peter"},{"first_name":"Niek","last_name":"Vasmel","full_name":"Vasmel, Niek"},{"full_name":"Waitukaitis, Scott R","id":"3A1FFC16-F248-11E8-B48F-1D18A9856A87","last_name":"Waitukaitis","orcid":"0000-0002-2299-3176","first_name":"Scott R"},{"full_name":"van Hecke, Martin","last_name":"van Hecke","first_name":"Martin"}],"publication_status":"published","article_processing_charge":"No","year":"2020","type":"journal_article","page":"63–68","day":"01","publication_identifier":{"eissn":["1745-2481"],"issn":["1745-2473"]},"article_type":"letter_note"}]