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 Binary to Continuous: Stochastic Re-Weighting for Robust Graph Explanation
Zhuomin Chen, Jingchao Ni, Hojat Allah Salehi +2
Graph Neural Networks (GNNs) have achieved remarkable performance in a wide range of graph-related learning tasks. However, explaining their predictions remains a challenging probl…
Exploring Multi-Modal Data with Tool-Augmented LLM Agents for Precise Causal Discovery
ChengAo Shen, Zhengzhang Chen, Dongsheng Luo +3
Causal discovery is an imperative foundation for decision-making across domains, such as smart health, AI for drug discovery and AIOps. Traditional statistical causal discovery met…
Explanation-Preserving Augmentation for Semi-Supervised Graph Representation Learning
Zhuomin Chen, Jingchao Ni, Hojat Allah Salehi +4
Self-supervised graph representation learning (GRL) typically generates paired graph augmentations from each graph to infer similar representations for augmentations of the same gr…