{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T22:57:17Z","timestamp":1769554637311,"version":"3.49.0"},"reference-count":46,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,12,5]],"date-time":"2023-12-05T00:00:00Z","timestamp":1701734400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,12,5]],"date-time":"2023-12-05T00:00:00Z","timestamp":1701734400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,12,5]]},"DOI":"10.1109\/icrc60800.2023.10386858","type":"proceedings-article","created":{"date-parts":[[2024,1,15]],"date-time":"2024-01-15T20:56:12Z","timestamp":1705352172000},"page":"1-10","source":"Crossref","is-referenced-by-count":13,"title":["Thermodynamic AI and the Fluctuation Frontier"],"prefix":"10.1109","author":[{"given":"Patrick J.","family":"Coles","sequence":"first","affiliation":[{"name":"Normal Computing Corporation,New York,New York,USA"}]},{"given":"Collin","family":"Szczepanski","sequence":"additional","affiliation":[{"name":"Normal Computing Corporation,New York,New York,USA"}]},{"given":"Denis","family":"Melanson","sequence":"additional","affiliation":[{"name":"Normal Computing Corporation,New York,New York,USA"}]},{"given":"Kaelan","family":"Donatella","sequence":"additional","affiliation":[{"name":"Normal Computing Corporation,New York,New York,USA"}]},{"given":"Antonio J.","family":"Martinez","sequence":"additional","affiliation":[{"name":"Normal Computing Corporation,New York,New York,USA"}]},{"given":"Faris","family":"Sbahi","sequence":"additional","affiliation":[{"name":"Normal Computing Corporation,New York,New York,USA"}]}],"member":"263","reference":[{"key":"ref1","article-title":"The forward-forward algorithm: Some preliminary investigations","author":"Hinton","year":"2022"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3467017"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/FPL.2009.5272262"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2018.2859237"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-04223-6"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/4.104196"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/72.129422"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/40.42986"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1063\/1.4818538"},{"key":"ref10","article-title":"Quantum computing and the entanglement frontier","author":"Preskill","year":"2012"},{"key":"ref11","article-title":"Natively probabilistic computation","volume-title":"Ph.D. dissertation","author":"Mansinghka","year":"2009"},{"key":"ref12","article-title":"Score-based generative modeling through stochastic differential equations","author":"Song","year":"2020"},{"key":"ref13","first-page":"6696","article-title":"Neural controlled differential equations for irregular time series","volume":"33","author":"Kidger","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref14","first-page":"1","article-title":"Scalable gradients and variational inference for stochastic differential equations","volume-title":"Symposium on Advances in Approximate Bayesian Inference","author":"Li"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-42553-1_3"},{"key":"ref16","first-page":"721","article-title":"Infinitely deep bayesian neural networks with stochastic differential equations","volume-title":"International Conference on Artificial Intelligence and Statistics","author":"Xu"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/bf02650179"},{"key":"ref18","article-title":"Thermodynamic computing","author":"Conte","year":"2019"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.3390\/e22030256"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3390\/e24060744"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICRC.2017.8123676"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICRC2020.2020.00012"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICRC.2018.8638594"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1088\/1367-2630\/ac4309"},{"key":"ref25","article-title":"Therml: Thermodynamics of machine learning","author":"Alemi","year":"2018"},{"key":"ref26","first-page":"2256","article-title":"Deep unsupervised learning using nonequilibrium thermodynamics","volume-title":"Proceedings of the 32nd International Conference on Machine Learning","volume":"37","author":"Sohl-Dickstein"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1103\/physrevlett.118.010601"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-conmatphys-031119-050745"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2006.49"},{"key":"ref30","article-title":"Noise can be helpful for variational quantum algorithms","author":"Liu","year":"2022"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1063\/1.5055860"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/IEDM45625.2022.10019548"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1038\/s41928-022-00774-2"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3261988"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevApplied.17.044046"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICRC60800.2023.10386858"},{"key":"ref37","article-title":"Church: a language for generative models","author":"Goodman","year":"2012"},{"key":"ref38","article-title":"Combinational stochastic logic","volume-title":"uS Patent","author":"Mansinghka","year":"2013"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1119\/1.16385"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/0038-1101(72)90119-0"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1103\/physrevlett.92.130601"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.2478\/v10187-010-0036-1"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.116.050401"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0046800"},{"key":"ref45","first-page":"4629","article-title":"What are Bayesian neural network posteriors really like?","volume-title":"International conference on machine learning","author":"Izmailov"},{"key":"ref46","first-page":"6840","article-title":"Denoising diffusion probabilistic models","volume":"33","author":"Ho","year":"2020","journal-title":"Advances in Neural Information Processing Systems"}],"event":{"name":"2023 IEEE International Conference on Rebooting Computing (ICRC)","location":"San Diego, CA, USA","start":{"date-parts":[[2023,12,5]]},"end":{"date-parts":[[2023,12,6]]}},"container-title":["2023 IEEE International Conference on Rebooting Computing (ICRC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10385233\/10386130\/10386858.pdf?arnumber=10386858","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,18]],"date-time":"2024-01-18T01:27:59Z","timestamp":1705541279000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10386858\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,5]]},"references-count":46,"URL":"https:\/\/doi.org\/10.1109\/icrc60800.2023.10386858","relation":{},"subject":[],"published":{"date-parts":[[2023,12,5]]}}}