{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T07:10:06Z","timestamp":1750749006101,"version":"3.41.0"},"reference-count":19,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,5,5]],"date-time":"2025-05-05T00:00:00Z","timestamp":1746403200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,5,5]],"date-time":"2025-05-05T00:00:00Z","timestamp":1746403200000},"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":[[2025,5,5]]},"DOI":"10.1109\/cscwd64889.2025.11033282","type":"proceedings-article","created":{"date-parts":[[2025,6,23]],"date-time":"2025-06-23T17:24:40Z","timestamp":1750699480000},"page":"1569-1574","source":"Crossref","is-referenced-by-count":0,"title":["A Variable Adaptive Embedding Transformer for Multivariate Time Series Forecasting"],"prefix":"10.1109","author":[{"given":"Yang","family":"Yang","sequence":"first","affiliation":[{"name":"School of Information, North China University of Technology,Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data,Beijing,China,100144"}]},{"given":"Weilong","family":"Ding","sequence":"additional","affiliation":[{"name":"School of Information, North China University of Technology,Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data,Beijing,China,100144"}]},{"given":"Qi","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Information, North China University of Technology,Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data,Beijing,China,100144"}]},{"given":"Yuwei","family":"Gu","sequence":"additional","affiliation":[{"name":"School of Information, North China University of Technology,Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data,Beijing,China,100144"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2024.3415615"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3627673.3679571"},{"key":"ref3","article-title":"N-beats: Neural basis expansion analysis for interpretable time series forecasting","author":"Boris","year":"2019","journal-title":"ICLR"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i9.26317"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2019.08.026"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/9354273"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3210006"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2019.07.001"},{"key":"ref9","article-title":"Timesnet: Temporal 2d-variation modeling for general time series analysis","author":"Wu","year":"2024","journal-title":"ICLR"},{"key":"ref10","first-page":"5816","article-title":"Scinet: Time series modeling and forecasting with sample convolution and interaction","volume-title":"NIPS","volume":"35","author":"Liu","year":"2022"},{"journal-title":"A Vaswani. Attention is all you need. NIPS","year":"2017","key":"ref11"},{"key":"ref12","first-page":"22419","article-title":"Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting","volume":"34","author":"Wu","year":"2021","journal-title":"NIPS"},{"key":"ref13","first-page":"27268","article-title":"Fedformer: Frequency enhanced decomposed transformer for long-term series forecasting","author":"Zhou","year":"2022","journal-title":"ICLR"},{"key":"ref14","article-title":"Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting","author":"Zhang","year":"2023","journal-title":"ICLR"},{"key":"ref15","article-title":"Revitalizing multivariate time series forecasting: Learnable decomposition with inter-series dependencies and intra-series variations modeling","author":"Yu","year":"2024","journal-title":"ICML"},{"key":"ref16","article-title":"itransformer: Inverted transformers are effective for time series forecasting","author":"Liu","year":"2024","journal-title":"ICLR"},{"volume-title":"arXiv preprint","year":"2016","author":"Hendrycks","key":"ref17"},{"key":"ref18","first-page":"9881","article-title":"Non-stationary transformers: Exploring the stationarity in time series fore-casting","volume":"35","author":"Liu","year":"2022","journal-title":"NIPS"},{"key":"ref19","article-title":"Long-term forecasting with tide: Time-series dense encoder","author":"Das","year":"2023","journal-title":"Transactions on Machine Learning Research"}],"event":{"name":"2025 28th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","start":{"date-parts":[[2025,5,5]]},"location":"Compiegne, France","end":{"date-parts":[[2025,5,7]]}},"container-title":["2025 28th International Conference on Computer Supported Cooperative Work in Design (CSCWD)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11033175\/11033221\/11033282.pdf?arnumber=11033282","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T06:31:31Z","timestamp":1750746691000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11033282\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,5]]},"references-count":19,"URL":"https:\/\/doi.org\/10.1109\/cscwd64889.2025.11033282","relation":{},"subject":[],"published":{"date-parts":[[2025,5,5]]}}}