{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T16:57:47Z","timestamp":1779296267573,"version":"3.51.4"},"reference-count":37,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"11","license":[{"start":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T00:00:00Z","timestamp":1698796800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001711","name":"ERA-NET CHIST-ERA Programme by the Swiss National Science Foundation","doi-asserted-by":"publisher","award":["20CH21_186999\/1"],"award-info":[{"award-number":["20CH21_186999\/1"]}],"id":[{"id":"10.13039\/501100001711","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2023,11]]},"DOI":"10.1109\/tnnls.2022.3153985","type":"journal-article","created":{"date-parts":[[2022,3,16]],"date-time":"2022-03-16T19:36:46Z","timestamp":1647459406000},"page":"8894-8908","source":"Crossref","is-referenced-by-count":48,"title":["Online Spatio-Temporal Learning in Deep Neural Networks"],"prefix":"10.1109","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5456-9441","authenticated-orcid":false,"given":"Thomas","family":"Bohnstingl","sequence":"first","affiliation":[{"name":"IBM Research Zurich, Rüschlikon, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7282-3792","authenticated-orcid":false,"given":"Stanis\u0142aw","family":"Wo\u017aniak","sequence":"additional","affiliation":[{"name":"IBM Research Zurich, Rüschlikon, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4720-4038","authenticated-orcid":false,"given":"Angeliki","family":"Pantazi","sequence":"additional","affiliation":[{"name":"IBM Research Zurich, Rüschlikon, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3826-5931","authenticated-orcid":false,"given":"Evangelos","family":"Eleftheriou","sequence":"additional","affiliation":[{"name":"IBM Research Zurich, Rüschlikon, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.psych.49.1.43"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/5.58356"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6638947"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8682336"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2012-65"},{"key":"ref6","first-page":"1412","article-title":"Slayer: Spike layer error reassignment in time","volume-title":"Proc. NIPS","author":"Shrestha"},{"key":"ref7","first-page":"787","article-title":"Long short-term memory and learning-to-learn in networks of spiking neurons","volume-title":"Proc. NIPS","author":"Bellec"},{"key":"ref8","article-title":"Deep learning incorporating biologically-inspired neural dynamics","author":"Wo\u017aniak","year":"2018","journal-title":"arXiv:1812.07040"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2019.2931595"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-020-0187-0"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/5.58337"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-45528-0"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-17236-y"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1989.1.2.270"},{"key":"ref15","article-title":"Unbiased online recurrent optimization","volume-title":"Proc. ICLR","author":"Tallec"},{"key":"ref16","first-page":"6594","article-title":"Approximating real-time recurrent learning with random Kronecker factors","volume-title":"Proc. NIPS","author":"Mujika"},{"key":"ref17","first-page":"604","article-title":"Optimal Kronecker-sum approximation of real time recurrent learning","volume-title":"Proc. ICML","author":"Benzing"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.conb.2019.01.011"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2020.00424"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1162\/neco_a_01086"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.43299"},{"key":"ref22","article-title":"A unified framework of online learning algorithms for training recurrent neural networks","author":"Marschall","year":"2019","journal-title":"arXiv:1907.02649"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.3389\/fncir.2018.00053"},{"key":"ref24","first-page":"5067","article-title":"An online sequence-to-sequence model using partial conditioning","volume-title":"Proc. NIPS","author":"Jaitly"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ASRU46091.2019.9003906"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.tics.2004.07.008"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.0010042"},{"key":"ref28","article-title":"Quasi-recurrent neural networks","volume-title":"Proc. ICLR","author":"Bradbury"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms13276"},{"key":"ref30","first-page":"1037","article-title":"Direct feedback alignment provides learning in deep neural networks","volume-title":"Proc. NIPS","author":"N\u00f8kland"},{"key":"ref31","article-title":"Towards efficient end-to-end speech recognition with biologically-inspired neural networks","author":"Bohnstingl","year":"2021","journal-title":"arXiv:2110.02743"},{"key":"ref32","first-page":"1881","article-title":"Modeling temporal dependencies in high-dimensional sequences: Application to polyphonic music generation and transcription","volume-title":"Proc. ICML","author":"Boulanger-Lewandowski"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.21236\/ADA273556"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.6028\/nist.ir.4930"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2016.2582924"},{"key":"ref37","volume-title":"Gradient-Based Learning Algorithms for Recurrent Networks and Their Computational Complexity","author":"Williams","year":"1995"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/10299535\/09736444.pdf?arnumber=9736444","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,18]],"date-time":"2024-01-18T00:13:34Z","timestamp":1705536814000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9736444\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11]]},"references-count":37,"journal-issue":{"issue":"11"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2022.3153985","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11]]}}}