MLSP-P30.7
A COMPARATIVE STUDY ON HOW DATA NORMALIZATION AFFECTS ZERO-SHOT GENERALIZATION IN TIME SERIES FOUNDATION MODELS
Ihab Ahmed, Siemens AG, LMU (Munich), Germany; Denis Krompaß, Cheng Feng, Siemens AG, Germany; Volker Tresp, LMU (Munich), China
Session:
MLSP-P30: Deep Learning for Time Series Analysis III Poster
Track:
Machine Learning for Signal Processing [ML]
Location:
Poster Area 8
Presentation Time:
Wed, 6 May, 14:00 - 16:00
Presentation
Discussion
Resources
No resources available.
Session MLSP-P30
MLSP-P30.1: TS-Agent: Reinforcement Learning Empowered LLM Agents for Financial Time Series Forecasting
Jiahong Zhu, Liaoning Technical University, China; Shuo Yin, Tsinghua University, China; Tianlong Yang, Liaoning Technical University, China; Yuqiao Liu, The Hong Kong University of Science and Technology, China
MLSP-P30.2: BEYOND THE WINDOW: REGION-BASED ANOMALY LOCALIZATION NETWORK FOR TIME SERIES ANOMALY DETECTION
Shinwoo Ham, Hyuntaek Jung, Eun Yi Kim, Artificial Intelligence & Computer Vision Lab., Konkuk University, Korea, Republic of
MLSP-P30.3: DPFAN: DUAL-PATH FEATURE-ADAPTIVE NETWORK FOR KPI ANOMALY DETECTION
Yiyun Zhang, Haodong Zheng, Songlei Jian, Yuan Yuan, Kai Lu, National University of Defense Technology, China
MLSP-P30.4: DPANet: Dual Pyramid Attention Network for Multivariate Time Series Forecasting
Qianyang Li, Xingjun Zhang, Shaoxun Wang, Xi'an Jiaotong University, China; Jia Wei, Tsinghua University, China
MLSP-P30.5: A MOUSE DYNAMICS AUTHENTICATION SYSTEM WITH A RECURRENCE PLOT IMAGE REPRESENTATION AND A VISION TRANSFORMER FRAMEWORK
Kaushik Mazumdar, Suresh Sundaram, INDIAN INSTITUTE OF TECHNOLOGY, GUWAHATI, India
MLSP-P30.6: GRAPH NEURAL NETWORKS WITH DIVERSITY-AWARE NEIGHBOR SELECTION AND DYNAMIC MULTI-SCALE FUSION FOR MULTIVARIATE TIME SERIES FORECASTING
Jingqi Xu, University of Southern California, United States of America; Guibin Chen, New York University, United States of America; Jingxi Lu, University of Southern California, United States of America; Yuzhang Lin, New York University, United States of America
MLSP-P30.7: A COMPARATIVE STUDY ON HOW DATA NORMALIZATION AFFECTS ZERO-SHOT GENERALIZATION IN TIME SERIES FOUNDATION MODELS
Ihab Ahmed, Siemens AG, LMU (Munich), Germany; Denis Krompaß, Cheng Feng, Siemens AG, Germany; Volker Tresp, LMU (Munich), China
MLSP-P30.8: WINDMOE: MIXTURE-OF-EXPERTS METHOD FOR WIND POWER FORECASTING UNDER EXTREME WEATHER CONDITIONS
Lei Liu, Qi Wang, Hongwei Zhao, Ruibo Guo, Jiahui Huang, Tengyuan Liu, Bin Li, University of Science and Technology of China, China
MLSP-P30.9: Homomorphic-Controlled Augmentation for Time Series Forecasting
Hu Li, Lin Cheng, Xinyuan Liu, University of Chinese Academy of Science, China; Zichen Liu, Long Long, Yucheng Zhang, Feng Dai, Institute of Computing Technology, Chinese Academy of Sciences, China
MLSP-P30.10: ONLINE CURSIVE HANDWRITING GENERATION USING TRACE TRANSFORMATION AND SYMBOL-INDEPENDENT POINT CLASSIFICATION MODEL
Karina Korovai, Nataliya Sakhnenko, Oleg Yakovchuk, Dmytro Zhelezniakov, Andrii Kroitor, Vadym Honcharenko, Olga Radyvonenko, Samsung R&D Institute Ukraine, Ukraine
Contacts