{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T09:03:40Z","timestamp":1765357420963},"reference-count":52,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,6,18]],"date-time":"2023-06-18T00:00:00Z","timestamp":1687046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,6,18]],"date-time":"2023-06-18T00:00:00Z","timestamp":1687046400000},"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":[[2023,6,18]]},"DOI":"10.1109\/ijcnn54540.2023.10191614","type":"proceedings-article","created":{"date-parts":[[2023,8,2]],"date-time":"2023-08-02T17:30:03Z","timestamp":1690997403000},"page":"1-10","source":"Crossref","is-referenced-by-count":5,"title":["Time series prediction and anomaly detection with recurrent spiking neural networks"],"prefix":"10.1109","author":[{"given":"Yann","family":"Cherdo","sequence":"first","affiliation":[{"name":"Renault Software LEAT, CNRS UMR 7248,Biot,France"}]},{"given":"Benoit","family":"Miramond","sequence":"additional","affiliation":[{"name":"University Cote d'Azur LEAT, CNRS UMR 7248,Biot,France"}]},{"given":"Alain","family":"Pegatoquet","sequence":"additional","affiliation":[{"name":"University Cote d'Azur LEAT, CNRS UMR 7248,Biot,France"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-48057-2_9"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref15","article-title":"Multivariate industrial time series with cyber-attack simulation: Fault detection using an LSTM-based predictive data model","author":"filonov","year":"2016","journal-title":"ArXiv"},{"key":"ref14","article-title":"Long Short Term Memory Networks for Anomaly Detection in Time Series","author":"malhotra","year":"0","journal-title":"Proc European Symposium on ANN"},{"journal-title":"MeteoNet An Open Reference Weather Dataset by Meteo-France","year":"2020","author":"larvor","key":"ref52"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2014.01.008"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2886457"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9053744"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/DSAA.2015.7344872"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN55064.2022.9892939"},{"journal-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling","year":"2014","author":"chung","key":"ref18"},{"journal-title":"Yahoo! webscope research","article-title":"s5 - a labeled anomaly detection dataset, version 1.0(16m)","year":"0","key":"ref51"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2015.141"},{"key":"ref46","article-title":"Properties of sparse distributed representations and their application to hierarchical temporal memory","author":"ahmad","year":"2015","journal-title":"ArXiv Preprint"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-022-00480-w"},{"key":"ref48","doi-asserted-by":"crossref","DOI":"10.1109\/MM.2018.112130359","article-title":"Loihi: A neuromorphic manycore processor with on-chip learning","author":"davies","year":"2018","journal-title":"IEEE Micro"},{"journal-title":"How can we be so dense? the benefits of using highly sparse representations","year":"2019","key":"ref47"},{"key":"ref42","article-title":"year=2004","author":"hawkins","year":"0","journal-title":"Intelligence"},{"key":"ref41","article-title":"Self-supervised learning of event-based optical flow with spiking neural networks","author":"hagenaars","year":"2021","journal-title":"Adv in Neural Information Processing Systems"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/72.279181"},{"journal-title":"The Cerebral Code Thinking a Thought in the Mosaics of the Mind","year":"1998","author":"calvin","key":"ref43"},{"journal-title":"PyTorch","year":"0","key":"ref49"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2788611"},{"journal-title":"Etsy skyline Online Code Repos","year":"2013","author":"stanway","key":"ref7"},{"key":"ref9","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2017.04.070","article-title":"Unsupervised real-time anomaly detection for streaming data","author":"ahmad","year":"2017","journal-title":"Neurocomputing"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3407197.3407225"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2019.2931595"},{"journal-title":"Twitter\/AnomalyDetection","year":"2015","author":"kejariwal","key":"ref6"},{"key":"ref5","article-title":"Robust random cut forest based anomaly detection on streams","author":"guha","year":"0","journal-title":"ICML 2016"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-021-00397-w"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109568"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN52387.2021.9533514"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2020.102170"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN55064.2022.9892618"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/s11063-021-10562-2"},{"journal-title":"Training spiking neural networks using lessons from deep learning","year":"2021","author":"eshraghian","key":"ref30"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/AICAS51828.2021.9458403"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4615-4831-7_19"},{"key":"ref2","article-title":"An analytical estimation of spiking neural networks energy efficiency","author":"lemaire","year":"2022","journal-title":"ArXiv Preprint"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511815706"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-15934-3_30"},{"key":"ref38","article-title":"Temporal pulses driven spiking neural network for fast object recognition in autonomous driving","author":"wang","year":"2020","journal-title":"ArXiv Preprint"},{"key":"ref24","article-title":"Long short-term memory and learning-to-learn in networks of spiking neurons","author":"bellec","year":"2018","journal-title":"Adv in Neural Information Processing Systems"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2005.1556240"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2022.918793"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2021.02.017"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(97)00011-7"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1038\/nn.4243"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2003.820440"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2021.116842"},{"key":"ref27","article-title":"Towards energy-efficient, low-latency and accurate spiking LSTMs","author":"datta","year":"2022","journal-title":"ArXiv Preprint"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107656"}],"event":{"name":"2023 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2023,6,18]]},"location":"Gold Coast, Australia","end":{"date-parts":[[2023,6,23]]}},"container-title":["2023 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10190990\/10190992\/10191614.pdf?arnumber=10191614","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,21]],"date-time":"2023-08-21T17:43:36Z","timestamp":1692639816000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10191614\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,18]]},"references-count":52,"URL":"https:\/\/doi.org\/10.1109\/ijcnn54540.2023.10191614","relation":{},"subject":[],"published":{"date-parts":[[2023,6,18]]}}}