Yikang Chen

Research Interest

Keywords: Causality, Generative Models
Topics: Counterfactual Reasoning, Causal Discovery, Causal Representation Learning

My research centers on empowering deep generative models to learn causal representations and conduct reliable causal inference, achieved through simple yet effective assumptions and novel model designs, finally applying these advancements to address real-world challenges.

Publications

Causal Discovery via Quantile Partial Effect

Chen, Y. Sun, X. Du, D.

ICML 2026 (Poster)

causal discovery functional causal model quantile partial effect

BIB PDF CODE

Exogenous Isomorphism for Counterfactual Identifiability

Chen, Y. Du, D.

ICML 2025 (Main Track, Spotlight Poster)

causal inference counterfactual identifiablity normalizing flow

BIB PDF CODE

ERCI: An Explainable Experience Replay Approach with Causal Inference for Deep Reinforcement Learning

Wang, J. Du, D. Tian, L. Chen, Y. Li, Y. Li, Y.

AAAI 2025 (AI Alignment Track, Oral)

causal inference reinforcement learning experience replay

BIB PDF

Exogenous Matching: Learning Good Proposals for Tractable Counterfactual Estimation

Chen, Y. Du, D. Tian, L.

NeurIPS 2024 (Main Track, Poster)

causal inference counterfactual reasoning importance sampling

BIB PDF CODE