| Residential College | false |
| Status | 已發表Published |
| Frequency-domain MLPs are More Effective Learners in Time Series Forecasting | |
Kun Yi1; Qi Zhang2 ; Wei Fan3; Shoujin Wang4; Pengyang Wang5 ; Hui He1; Defu Lian6; Ning An7; Longbing Cao8; Zhendong Niu11
| |
| 2023-12 | |
| Conference Name | Thirty-seventh Conference on Neural Information Processing Systems |
| Conference Date | 2023-12-12 |
| Conference Place | New Orleans, USA |
| Document Type | Conference paper |
| Collection | THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU) |
| Corresponding Author | Qi Zhang |
| Affiliation | 1.Beijing Institute of Technology 2.Tongji University 3.University of Oxford 4.University of Technology Sydney 5.SKL-IOTSC. University of Macau 6.USTC 7.HeFei University of Technology 8.Macquarie University |
| Recommended Citation GB/T 7714 | Kun Yi,Qi Zhang,Wei Fan,et al. Frequency-domain MLPs are More Effective Learners in Time Series Forecasting[C], 2023. |
| APA | Kun Yi., Qi Zhang., Wei Fan., Shoujin Wang., Pengyang Wang., Hui He., Defu Lian., Ning An., Longbing Cao., & Zhendong Niu1 (2023). Frequency-domain MLPs are More Effective Learners in Time Series Forecasting. . |
| Files in This Item: | There are no files associated with this item. | |||||
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