{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T06:23:02Z","timestamp":1774419782266,"version":"3.50.1"},"reference-count":36,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,4,6]],"date-time":"2025-04-06T00:00:00Z","timestamp":1743897600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,4,6]],"date-time":"2025-04-06T00:00:00Z","timestamp":1743897600000},"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":[[2025,4,6]]},"DOI":"10.1109\/icassp49660.2025.10888630","type":"proceedings-article","created":{"date-parts":[[2025,3,12]],"date-time":"2025-03-12T17:15:02Z","timestamp":1741799702000},"page":"1-5","source":"Crossref","is-referenced-by-count":1,"title":["TCTformer: Long-term forecasting with dual attention transformers"],"prefix":"10.1109","author":[{"given":"Long","family":"Sun","sequence":"first","affiliation":[{"name":"Ocean University of China,College of Information Science and Engineering"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyan","family":"Gao","sequence":"additional","affiliation":[{"name":"Ocean University of China,College of Information Science and Engineering"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kai","family":"Xia","sequence":"additional","affiliation":[{"name":"Ocean University of China,College of Information Science and Engineering"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuwei","family":"Hu","sequence":"additional","affiliation":[{"name":"Ocean University of China,College of Information Science and Engineering"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuan","family":"Feng","sequence":"additional","affiliation":[{"name":"Ocean University of China,College of Information Science and Engineering"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","author":"Liu","year":"2023","journal-title":"itransformer: Inverted transformers are effective for time series forecasting"},{"key":"ref2","article-title":"Forecasting treatment responses over time using recurrent marginal structural networks","volume":"31","author":"Lim","year":"2018","journal-title":"Advances in neural information processing systems"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403118"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.14778\/3489496.3489503"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP39728.2021.9413914"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108218"},{"key":"ref7","volume-title":"Time series analysis: forecasting and control.","author":"Box","year":"2015"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1017\/9781108164818"},{"key":"ref9","author":"Bahdanau","year":"2014","journal-title":"Neural machine translation by jointly learning to align and translate"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.113"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3210006"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2019.07.001"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1038\/323533a0"},{"key":"ref15","author":"Li","year":"2017","journal-title":"Diffusion convolutional recurrent neural network: Data-driven traffic forecasting"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/505"},{"key":"ref17","first-page":"17766","article-title":"Spectral temporal graph neural network for multivariate time-series forecasting","volume":"33","author":"Cao","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP48485.2024.10448209"},{"key":"ref19","author":"Kipf","year":"2016","journal-title":"Semi-supervised classification with graph convolutional networks"},{"key":"ref20","article-title":"Attention is all you need","author":"Vaswani","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref21","author":"Devlin","year":"2018","journal-title":"Bert: Pre-training of deep bidirectional transformers for language understanding"},{"key":"ref22","author":"Dosovitskiy","year":"2020","journal-title":"An image is worth 16x16 words: Transformers for image recognition at scale"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20053-3_5"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2018.8462506"},{"key":"ref25","article-title":"Enhancing the locality and breaking the memory bottleneck of transformer on time series forecasting","volume":"32","author":"Li","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17325"},{"key":"ref27","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":"ref28","first-page":"27268","article-title":"Fedformer: Frequency enhanced decomposed transformer for long-term series forecasting","volume-title":"International conference on machine learning","author":"Zhou"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN60899.2024.10651438"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i9.26317"},{"key":"ref31","author":"Nie","year":"2022","journal-title":"A time series is worth 64 words: Long-term forecasting with transformers"},{"key":"ref32","article-title":"Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting","volume-title":"The eleventh international conference on learning representations","author":"Zhang"},{"key":"ref33","author":"Bai","year":"2018","journal-title":"An empirical evaluation of generic convolutional and recurrent networks for sequence modeling"},{"key":"ref34","author":"Das","year":"2023","journal-title":"Long-term forecasting with tide: Time-series dense encoder"},{"key":"ref35","author":"Wu","year":"2022","journal-title":"Timesnet: Temporal 2d-variation modeling for general time series analysis"},{"key":"ref36","first-page":"9881","article-title":"Non-stationary transformers: Exploring the stationarity in time series forecasting","volume":"35","author":"Liu","year":"2022","journal-title":"Advances in Neural Information Processing Systems"}],"event":{"name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","location":"Hyderabad, India","start":{"date-parts":[[2025,4,6]]},"end":{"date-parts":[[2025,4,11]]}},"container-title":["ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10887540\/10887541\/10888630.pdf?arnumber=10888630","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T05:24:40Z","timestamp":1774416280000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10888630\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,6]]},"references-count":36,"URL":"https:\/\/doi.org\/10.1109\/icassp49660.2025.10888630","relation":{},"subject":[],"published":{"date-parts":[[2025,4,6]]}}}