Chao Che — accepted AI-conference papers

2025

Subgraph Information Bottleneck with Causal Dependency for Stable Molecular Relational Learning

Peiliang Zhang, Jingling Yuan, Chao Che, Yongjun Zhu, Lin Li

IJCAI 2025

Molecular Relational Learning (MRL) is widely applied in molecular sciences. Recent studies attempt to retain molecular core information (e.g., substructures) by Graph Information Bottleneck but primarily focus on information compression without considering the causal dependencies of chemical reacti

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2024

SCAT: A Time Series Forecasting with Spectral Central Alternating Transformers

Chengjie Zhou, Chao Che, Pengfei Wang, Qiang Zhang

IJCAI 2024poster

Time series forecasting has essential applications across various domains. For instance, forecasting power time series can optimize energy usage and bolster grid stability and reliability. Existing models based on transformer architecture are limited to classical design, ignoring the impact of spati…

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