3 papers
cs.LG2026
Causal Discovery for Irregularly Time Series with Consistency Guarantees
Weihong Li, Baohong Li, Anpeng Wu +4
This paper studies causal discovery in irregularly sampled time series-a key challenge in risk-sensitive domains like finance, healthcare, and climate science, where missing data a…
cs.LG2025
Sequential Treatment Effect Estimation with Unmeasured Confounders
Yingrong Wang, Anpeng Wu, Baohong Li +4
This paper studies the cumulative causal effects of sequential treatments in the presence of unmeasured confounders. It is a critical issue in sequential decision-making scenarios…
cs.CL2024
Causality for Large Language Models
Anpeng Wu, Kun Kuang, Minqin Zhu +7
Recent breakthroughs in artificial intelligence have driven a paradigm shift, where large language models (LLMs) with billions or trillions of parameters are trained on vast datase…