| 2026 | AAAI | Revisiting Differentiable Structure Learning: Inconsistency of L1 Penalty and Beyond. | Kaifeng Jin, Ignavier Ng, Kun Zhang, Biwei Huang |
| 2026 | ACL | C-World: A Computer Use Agent Environment Creator. | Ziqiao Xi, Shuang Liang, Qi Liu, Jiaqing Zhang, Letian Peng, Fang Nan, Meshal Nayim, Tianhui Zhang, Rishika Mundada, Lianhui Qin, Biwei Huang, Kun Zhou |
| 2026 | ACL | Hybrid Self-evolving Structured Memory for Computer-Use Agents. | Sibo Zhu, Wenyi Wu, Kun Zhou, Stephen Wang, Biwei Huang |
| 2025 | ICLR | Analytic DAG Constraints for Differentiable DAG Learning. | Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Mingming Gong, Biwei Huang, Kun Zhang, Anton van den Hengel, Javen Qinfeng Shi |
| 2025 | ICLR | A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery. | Yingyu Lin, Yuxing Huang, Wenqin Liu, Haoran Deng, Ignavier Ng, Kun Zhang, Mingming Gong, Yian Ma, Biwei Huang |
| 2025 | ICLR | Differentiable Causal Discovery for Latent Hierarchical Causal Models. | Parjanya Prajakta Prashant, Ignavier Ng, Kun Zhang, Biwei Huang |
| 2025 | ICLR | Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning. | Xinyue Wang, Biwei Huang |
| 2025 | ICLR | Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations. | Yupei Yang, Biwei Huang, Fan Feng, Xinyue Wang, Shikui Tu, Lei Xu |
| 2025 | ICML | MissScore: High-Order Score Estimation in the Presence of Missing Data. | Wenqin Liu, Haoze Hou, Erdun Gao, Biwei Huang, Qiuhong Ke, Howard D. Bondell, Mingming Gong |
| 2024 | AAAI | ACAMDA: Improving Data Efficiency in Reinforcement Learning through Guided Counterfactual Data Augmentation. | Yuewen Sun, Erli Wang, Biwei Huang, Chaochao Lu, Lu Feng, Changyin Sun, Kun Zhang |
| 2024 | ICLR | A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables. | Xinshuai Dong, Biwei Huang, Ignavier Ng, Xiangchen Song, Yujia Zheng, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang |
| 2024 | ICLR | Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability. | Songyao Jin, Feng Xie, Guangyi Chen, Biwei Huang, Zhengming Chen, Xinshuai Dong, Kun Zhang |
| 2024 | ICLR | Federated Causal Discovery from Heterogeneous Data. | Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang |
| 2024 | ICLR | Identifiable Latent Polynomial Causal Models through the Lens of Change. | Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi |
| 2024 | ICML | An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series. | Qiang Huang, Chuizheng Meng, Defu Cao, Biwei Huang, Yi Chang, Yan Liu |
| 2024 | ICML | Score-Based Causal Discovery of Latent Variable Causal Models. | Ignavier Ng, Xinshuai Dong, Haoyue Dai, Biwei Huang, Peter Spirtes, Kun Zhang |
| 2024 | ICML | Optimal Kernel Choice for Score Function-based Causal Discovery. | Wenjie Wang, Biwei Huang, Feng Liu, Xinge You, Tongliang Liu, Kun Zhang, Mingming Gong |
| 2024 | IJCAI | Boosting Efficiency in Task-Agnostic Exploration through Causal Knowledge. | Yupei Yang, Biwei Huang, Shikui Tu, Lei Xu |
| 2022 | ICLR | AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning. | Biwei Huang, Fan Feng, Chaochao Lu, Sara Magliacane, Kun Zhang |
| 2022 | ICML | Action-Sufficient State Representation Learning for Control with Structural Constraints. | Biwei Huang, Chaochao Lu, Liu Leqi, Jos Miguel Hernndez-Lobato, Clark Glymour, Bernhard Schlkopf, Kun Zhang |
| 2022 | ICML | Identification of Linear Non-Gaussian Latent Hierarchical Structure. | Feng Xie, Biwei Huang, Zhengming Chen, Yangbo He, Zhi Geng, Kun Zhang |
| 2021 | AAAI | DeepTrader: A Deep Reinforcement Learning Approach for Risk-Return Balanced Portfolio Management with Market Conditions Embedding. | Zhicheng Wang, Biwei Huang, Shikui Tu, Kun Zhang, Lei Xu |
| 2020 | AAAI | Causal Discovery from Multiple Data Sets with Non-Identical Variable Sets. | Biwei Huang, Kun Zhang, Mingming Gong, Clark Glymour |
| 2019 | ICML | Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models. | Biwei Huang, Kun Zhang, Mingming Gong, Clark Glymour |
| 2018 | KDD | Generalized Score Functions for Causal Discovery. | Biwei Huang, Kun Zhang, Yizhu Lin, Bernhard Schlkopf, Clark Glymour |
| 2017 | ICDM | Behind Distribution Shift: Mining Driving Forces of Changes and Causal Arrows. | Biwei Huang, Kun Zhang, Jiji Zhang, Ruben Sanchez-Romero, Clark Glymour, Bernhard Schlkopf |
| 2017 | IJCAI | Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination. | Kun Zhang, Biwei Huang, Jiji Zhang, Clark Glymour, Bernhard Schlkopf |
| 2016 | UAI | On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection. | Kun Zhang, Jiji Zhang, Biwei Huang, Bernhard Schlkopf, Clark Glymour |
| 2015 | IJCAI | Identification of Time-Dependent Causal Model: A Gaussian Process Treatment. | Biwei Huang, Kun Zhang, Bernhard Schlkopf |