MLSP-L11.6
S2TX: CROSS-ATTENTION MULTI-SCALE STATE-SPACE TRANSFORMER FOR TIME SERIES FORECASTING
Zihao Wu, Haoming Yang, Juncheng Dong, Vahid Tarokh, Duke University, United States of America
Session:
MLSP-L11: Representation Learning for Time Series Forecasting Oral
Track:
Machine Learning for Signal Processing [ML]
Location:
Room 112
Presentation Time:
Wed, 6 May, 15:40 - 16:00
Presentation
Discussion
Resources
No resources available.
Session MLSP-L11
MLSP-L11.1: MPL-MOE: MULTI-MODAL PROMPT LEARNING WITH MIXTURE OF EXPERTS FOR MULTIVARIATE TIME SERIES FORECASTING
Rui Hou, Yao Liu, Jingbo Wang, Qiao Liu, Lanyi Zhang, Weiyi Zhou, University of Electronic Science and Technology of China, China
MLSP-L11.2: WaveFormer: Wavelet-Enhanced Transformer for Multi-Scale Representation Learning in Time Series Forecasting
Boya Zhang, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China; Longfei Liu, Nanjing University, China; Dan Wu, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China
MLSP-L11.3: PLUG-AND-PLAY TEMPORAL FOURIER EMBEDDING FOR ROBUST LONG-HORIZON TRAFFIC FLOW FORECASTING
Peng Wang, Hairui Sun, Kanghua Hui, Civil Aviation University of China, China
MLSP-L11.4: DEEP TPC: TEMPORAL-PRIOR CONDITIONING FOR TIME SERIES FORECASTING
Filippos Bellos, NaveenJohn Premkumar, University of Michigan, United States of America; Yannis Avrithis, Independent Scientist, United States of America; Nam Nguyen, Capital One, United States of America; Jason Corso, University of Michigan, United States of America
MLSP-L11.5: CHANNEL-WISE RETRIEVAL FOR MULTIVARIATE TIME SERIES FORECASTING
Junhyeok Kang, Jun Seo, Soyeon Park, Sangjun Han, Seohui Bae, Hyeokjun Choe, Soonyoung Lee, LG AI Research, Korea, Republic of
MLSP-L11.6: S2TX: CROSS-ATTENTION MULTI-SCALE STATE-SPACE TRANSFORMER FOR TIME SERIES FORECASTING
Zihao Wu, Haoming Yang, Juncheng Dong, Vahid Tarokh, Duke University, United States of America
Contacts