4 papers
SVTime: Small Time Series Forecasting Models Informed by "Physics" of Large Vision Model Forecasters
ChengAo Shen, Ziming Zhao, Hanghang Tong +4
Time series AI is crucial for analyzing dynamic web content, driving a surge of pre-trained large models known for their strong knowledge encoding and transfer capabilities across…
From Images to Signals: Are Large Vision Models Useful for Time Series Analysis?
Ziming Zhao, ChengAo Shen, Hanghang Tong +4
Transformer-based models have gained increasing attention in time series research, driving interest in Large Language Models (LLMs) and foundation models for time series analysis.…
Multi-Modal View Enhanced Large Vision Models for Long-Term Time Series Forecasting
ChengAo Shen, Wenchao Yu, Ziming Zhao +4
Time series, typically represented as numerical sequences, can also be transformed into images and texts, offering multi-modal views (MMVs) of the same underlying signal. These MMV…
Harnessing Vision Models for Time Series Analysis: A Survey
Jingchao Ni, Ziming Zhao, ChengAo Shen +5
Time series analysis has witnessed the inspiring development from traditional autoregressive models, deep learning models, to recent Transformers and Large Language Models (LLMs).…