{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T23:14:49Z","timestamp":1782256489998,"version":"3.54.5"},"reference-count":45,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Comunidad de Madrid and the Complutense University of Madrid","award":["2019-T1\/TIC-13298"],"award-info":[{"award-number":["2019-T1\/TIC-13298"]}]},{"name":"Comunidad de Madrid and the Complutense University of Madrid","award":["2019-T1\/TIC-12776"],"award-info":[{"award-number":["2019-T1\/TIC-12776"]}]},{"DOI":"10.13039\/100010784","name":"Banco Santander","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100010784","id-type":"DOI","asserted-by":"publisher"}]},{"name":"UCM","award":["PR44\/21-29937"],"award-info":[{"award-number":["PR44\/21-29937"]}]},{"name":"Ministerio de Economía y Competitividad, Agencia Estatal de Investigación and Fondo Europeo de Desarrollo Regional","award":["PID2021-125506NA-I00"],"award-info":[{"award-number":["PID2021-125506NA-I00"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1109\/tpami.2024.3495999","type":"journal-article","created":{"date-parts":[[2024,11,11]],"date-time":"2024-11-11T18:40:23Z","timestamp":1731350423000},"page":"1309-1316","source":"Crossref","is-referenced-by-count":4,"title":["Fast and Functional Structured Data Generators Rooted in Out-of-Equilibrium Physics"],"prefix":"10.1109","volume":"47","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2098-5743","authenticated-orcid":false,"given":"Alessandra","family":"Carbone","sequence":"first","affiliation":[{"name":"CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative-UMR 7238, Sorbonne Université, Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3017-0858","authenticated-orcid":false,"given":"Aur\u00e9lien","family":"Decelle","sequence":"additional","affiliation":[{"name":"Departamento de Física Teórica, Universidad Complutense de Madrid, Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6122-5252","authenticated-orcid":false,"given":"Lorenzo","family":"Rosset","sequence":"additional","affiliation":[{"name":"CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative-UMR 7238, Sorbonne Université, Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4007-9406","authenticated-orcid":false,"given":"Beatriz","family":"Seoane","sequence":"additional","affiliation":[{"name":"Departamento de Física Teórica, Universidad Complutense de Madrid, Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1207\/s15516709cog0901_7"},{"key":"ref2","article-title":"Explaining the effects of non-convergent sampling in the training of energy-based models","author":"Agoritsas","year":"2023"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-019-0598-1"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-04184-w"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.cels.2020.11.005"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.21468\/SciPostPhys.14.3.032"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1126\/science.aag2302"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6633\/aa9965"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1038\/nature15393"},{"key":"ref10","article-title":"Simple and controllable music generation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Copet"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-33126-x"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1209\/0295-5075\/119\/60001"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1088\/1674-1056\/abd160"},{"key":"ref14","first-page":"5345","article-title":"Equilibrium and non-equilibrium regimes in the learning of restricted Boltzmann machines","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Decelle"},{"key":"ref15","article-title":"Unsupervised hierarchical clustering using the learning dynamics of RBMs","author":"Decelle","year":"2023"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkab1045"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1103\/physrevx.13.021003"},{"key":"ref18","first-page":"2023","article-title":"Designing molecular RNA switches with restricted Boltzmann machines","author":"Cossio-Diaz","year":"2023","journal-title":"bioRxiv"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-03819-2"},{"issue":"1","key":"ref20","first-page":"643","article-title":"Learning algorithms for the classification restricted Boltzmann machine","volume":"13","author":"Larochelle","year":"2012","journal-title":"J. Mach. Learn. Res."},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref22","article-title":"A tutorial on energy-based learning","volume":"1","author":"LeCun","year":"2006","journal-title":"Predicting Structured Data"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1038\/s43588-022-00265-6"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1126\/science.ade2574"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1038\/s41567-019-0545-1"},{"key":"ref26","first-page":"2022","article-title":"Design in the dark: Learning deep generative models for De Novo protein design","author":"Moffat","year":"2022","journal-title":"bioRxiv"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1111471108"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-021-04441-9"},{"key":"ref29","article-title":"Evaluating large language models trained on medical data","volume":"6","author":"Natarajan","year":"2023","journal-title":"Nature"},{"key":"ref30","article-title":"MCMC should mix: Learning energy-based model with neural transport latent space MCMC","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Nijkamp"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5973"},{"key":"ref32","first-page":"5232","article-title":"Learning non-convergent non-persistent short-run MCMC toward energy-based model","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Nijkamp"},{"key":"ref33","article-title":"ChatGPT: A large language model","year":"2023"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btl104"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-22732-w"},{"key":"ref36","volume-title":"Information Processing in Dynamical Systems: Foundations of Harmony Theory","author":"Smolensky","year":"1987"},{"key":"ref37","first-page":"2256","article-title":"Deep unsupervised learning using nonequilibrium thermodynamics","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Sohl-Dickstein"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390290"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.39397"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1093\/molbev\/msac070"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0805923106"},{"key":"ref42","first-page":"2635","article-title":"A theory of generative convnet","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Xie"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.12.136"},{"key":"ref44","first-page":"2023","article-title":"Deep convolutional and conditional neural networks for large-scale genomic data generation","author":"Yelmen","year":"2023","journal-title":"bioRxiv"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1009303"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/34\/10835210\/10750287.pdf?arnumber=10750287","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,10]],"date-time":"2025-01-10T06:03:57Z","timestamp":1736489037000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10750287\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2]]},"references-count":45,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2024.3495999","relation":{},"ISSN":["0162-8828","2160-9292","1939-3539"],"issn-type":[{"value":"0162-8828","type":"print"},{"value":"2160-9292","type":"electronic"},{"value":"1939-3539","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2]]}}}