{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T08:01:53Z","timestamp":1772179313705,"version":"3.50.1"},"reference-count":56,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T00:00:00Z","timestamp":1762992000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T00:00:00Z","timestamp":1762992000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62202422,62372408"],"award-info":[{"award-number":["62202422,62372408"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,11,13]]},"DOI":"10.1109\/ickg66886.2025.00037","type":"proceedings-article","created":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:42:11Z","timestamp":1772138531000},"page":"229-236","source":"Crossref","is-referenced-by-count":0,"title":["M-TSINR: Multiscale Implicit Neural Representations via Mamba Encoder for Time Series Anomaly Detection"],"prefix":"10.1109","author":[{"given":"Ke","family":"Liu","sequence":"first","affiliation":[{"name":"College of Computer Science, Zhejiang University,Zhejiang Key Lab of Accessible Perception & Intelligent Systems,Hangzhou,Zhejiang,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengxuan","family":"Li","sequence":"additional","affiliation":[{"name":"College of Computer Science, Zhejiang University,Zhejiang Key Lab of Accessible Perception & Intelligent Systems,Hangzhou,Zhejiang,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qianqian","family":"Shen","sequence":"additional","affiliation":[{"name":"College of Computer Science, Zhejiang University,Zhejiang Key Lab of Accessible Perception & Intelligent Systems,Hangzhou,Zhejiang,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Gao","sequence":"additional","affiliation":[{"name":"College of Computer Science, Zhejiang University,Zhejiang Key Lab of Accessible Perception & Intelligent Systems,Hangzhou,Zhejiang,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haishuai","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer Science, Zhejiang University,Zhejiang Key Lab of Accessible Perception & Intelligent Systems,Hangzhou,Zhejiang,China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2023.3290202"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3313728"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.3390\/app12178902"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3589334.3645710"},{"key":"ref5","author":"Wu","year":"2022","journal-title":"Timesnet: Temporal 2d-variation modeling for general time series analysis"},{"key":"ref6","article-title":"One fits all: Power general time series analysis by pretrained lm","volume":"36","author":"Zhou","year":"2024","journal-title":"Advances in neural information processing systems"},{"key":"ref7","author":"Dupont","year":"2022","journal-title":"From data to functa: Your data point is a function and you can treat it like one"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00504"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3690624.3709266"},{"key":"ref10","author":"Jeong","year":"2022","journal-title":"Time-series anomaly detection with implicit neural representation"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-69143-1_21"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/SSP.2012.6319708"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2016.7729882"},{"key":"ref14","author":"Papadimitriou","year":"2005","journal-title":"Streaming pattern discovery in multiple time-series"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.envsoft.2009.08.010"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/1541880.1541882"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2017.08.032"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/INISTA.2011.5946052"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.cja.2022.05.001"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/342009.335388"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.17"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/2689746.2689747"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330672"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3164087"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2935975"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2886457"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i9.26317"},{"key":"ref28","author":"Xu","year":"2021","journal-title":"Anomaly transformer: Time series anomaly detection with association discrepancy"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICME55011.2023.00349"},{"key":"ref30","first-page":"11726","article-title":"Hilbert distillation for cross-dimensionality networks","volume":"35","author":"Qin","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01047"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i3.32336"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2025\/1027"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-73668-1_1"},{"key":"ref35","article-title":"A tensorized transformer for language modeling","volume":"32","author":"Ma","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"ref36","first-page":"3143","article-title":"Does bert rediscover a classical nlp pipeline?","volume-title":"Proceedings of the 29th International Conference on Computational Linguistics","author":"Niu","year":"2022"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72684-2_17"},{"key":"ref39","author":"Woo","year":"2022","journal-title":"Etsformer: Exponential smoothing transformers for time-series forecasting"},{"key":"ref40","first-page":"27268","article-title":"Fedformer: Frequency enhanced decomposed transformer for long-term series forecasting","volume-title":"International Conference on Machine Learning","author":"Zhou","year":"2022"},{"key":"ref41","author":"Gu","year":"2023","journal-title":"Mamba: Linear-time sequence modeling with selective state spaces"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2025.3610435"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.129178"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2025.3569596"},{"key":"ref45","author":"Gu","year":"2021","journal-title":"Efficiently modeling long sequences with structured state spaces"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467174"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219845"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-020-0495-6"},{"key":"ref49","volume-title":"Skoltech anomaly benchmark (skab)","author":"Katser","year":"2020"},{"key":"ref50","author":"Zhang","year":"2022","journal-title":"Less is more: Fast multivariate time series forecasting with light samplingoriented mlp structures"},{"key":"ref51","first-page":"22419","article-title":"Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting","volume":"34","author":"Wu","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref52","article-title":"Pyraformer: Low-complexity pyramidal attention for long-range time series modeling and forecasting","volume-title":"International conference on learning representations","author":"Liu","year":"2021"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17325"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.14778\/3551793.3551830"},{"key":"ref56","author":"Kingma","year":"2014","journal-title":"Adam: A method for stochastic optimization"}],"event":{"name":"2025 IEEE International Conference on Knowledge Graph (ICKG)","location":"Limassol, Cyprus","start":{"date-parts":[[2025,11,13]]},"end":{"date-parts":[[2025,11,14]]}},"container-title":["2025 IEEE International Conference on Knowledge Graph (ICKG)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11391635\/11391709\/11391891.pdf?arnumber=11391891","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T06:15:41Z","timestamp":1772172941000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11391891\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,13]]},"references-count":56,"URL":"https:\/\/doi.org\/10.1109\/ickg66886.2025.00037","relation":{},"subject":[],"published":{"date-parts":[[2025,11,13]]}}}