MLSP-P17: Deep Learning for Time Series Analysis I
Poster
Wed, 6 May, 09:00 - 11:00
Location: Poster Area 4
Session Type: Poster
Track: Machine Learning for Signal Processing [ML]
Click the to view the manuscript on IEEE Xplore Open Preview

MLSP-P17.1: PATCH FIRST, GENERATE THEN: A DEBIASED DIFFUSION MODEL FOR MULTIVARIATE TIME SERIES GENERATION
Qi Zhang, Li Lin, Xinrui Zhang, Kaiwen Xia, Xinyan Du, Shuai Wang, Southeast university, China

MLSP-P17.2: Frequency-Domain Driven Recurrent Attention with Linear Complexity for Time Series Forecasting
Jintao Li, Hui Deng, Jiang Xiao, Aojin Li, Sichen He, Shui Yu, University of Electronic Science and Technology of China, China

MLSP-P17.3: UNIFIED MODELING OF LAGGED AND SYNCHRONIZED RELATIONS IN MULTIVARIATE TIME SERIES FORECASTING
Yawen Liu, Ciyi Liu, Xinxing Zhou, Lei Xu, Yanlong Wen, Xiaojie Yuan, NanKaiUniversity, China

MLSP-P17.4: DFGA-Net: A Dual-Frequency Guided Attention Network for Multivariate Time Series Prediction
Zhijiang Wang, Chinese Academy of Sciences, China; Jing Wang, Southeast University, China; Enyi Cao, Beijing Jiaotong University, China; Yuqi Li, Chinese Academy of Sciences, China; Keyan Jin, Macao Polytechnic University, Macao

MLSP-P17.5: Unleashing the power of global-local synergy for multivariate time series forecasting
Jiacheng Zhang, Yukai Shi, Zhejiang Gongshang University, China; Xiaolan Yang, Guangdong Institute of Intelligence Science and Technology, China; Yemin Wang, Xiamen University, China; Jerome Yen, Xin Chen, The University of Macau, China; Qing Yu, Termi Tech, China; Xuhui Xie, National University of Defense Technology, China; Sheng Wang, Guangdong Institute of Intelligence Science and Technology, China

MLSP-P17.6: AdaNODEs: Test Time Adaptation for Time Series Forecasting Using Neural ODEs
Ting Dang, The University of Melbourne, Australia; Soumyajit Chatterjee, Nokia Bell Labs, United Kingdom of Great Britain and Northern Ireland; Hong Jia, The University of Auckland, New Zealand; Yu Wu, University of Cambridge, United Kingdom of Great Britain and Northern Ireland; Flora Salim, The University of New South Wales, Australia; Fahim Kawsar, University of Glasgow, United Kingdom of Great Britain and Northern Ireland

MLSP-P17.7: BIPOLAR RELATIONAL NETWORK FOR IRREGULAR TIME SERIES ANOMALY DETECTION
Xiaoyu Zhang, Xiaofeng Lu, Beijing University of Posts and Telecommunications, China; Peiheng Li, Nanjing Normal University, China; Minjiao Yang, Beijing University of Posts and Telecommunications, China; Yaru Zhao, University of International Relations, China

MLSP-P17.8: PI-TPDNET: A PHYSICS-INFORMED TREND-PERIOD DECOMPOSITION NEURAL NETWORK FOR AIR QUALITY PREDICTION
Shenghua Li, Qingyang Zhang, Jie Liu, Xiaowei Guo, Xinhai Chen, Qinglin Wang, National University of Defense Technology, China

MLSP-P17.9: GAUSSIAN LOCALITY PRIOR FOR CONTRAST–RECONSTRUCTION LEARNING:STATE–SPACE MODEL-BASED TIME–SERIES ANOMALY DETECTION
TIanli Han, Yutong Li, Siyu Zheng, Qingyun Xiong, Junqi Guo, Beijing Normal University, China

MLSP-P17.10: RAMTIME: RETRIEVAL-AUGMENTED MEMORY FOR TIME SERIES FORECASTING
Jie Li, Yiyan Wu, Harbin Institute of Technology, China