Biwei Huang - RankMe

123 papers A* 42A 1Journal 76Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Ability Transfer and Recovery via Modularized Parameters Localization. CoRR Songyao Jin, Kun Zhou, Wenqi Li, Peng Wang, Biwei Huang
2026	J	`jnl`	Beyond Explainable AI (XAI): An Overdue Paradigm Shift and Post-XAI Research Directions. CoRR Saleh Afroogh, Seyd Ishtiaque Ahmed, Petra Ahrweiler, David Alvarez-Melis, Mansur Maturidi Arief, Emilia Barakova, Falco J. Bargagli-Stoffi, Erdem Biyik, Hanjie Chen, Xiang 'Anthony' Chen, Robert Clements, Keeley Crockett, Amit Dhurandhar, Fethiye Irmak Dogan, Mollie Dollinger, Motahhare Eslami, Aldo A. Faisal, Arya Farahi, Melanie Fernandez Pradie, Saadia Gabrie, Diego Garcia-Olano, Marzyeh Ghassemi, Shaona Ghosh, Hatice Gunes, Ehsan Hajiramezanali, Stefan Haufe, Biwei Huang, Angel Hwang, Md Tauhidul Islam, Junfeng Jiao, Amir-Hossein Karimi, Saber Kazeminasab, Anastasia Kuzminykh, William G. La Cava, Brian Y. Lim, Xiaofeng Liu, Mohammad R. K. Mofrad, Alicia Parrish, María Pérez-Ortiz, Shriti Raj, Swabha Swayamdipta, Salmon Talebi, Kush R. Varshney, Mihaela Vorvoreanu, Lily Weng, Alice Xiang, Yiming Xu, Ding Zhao, Jieyu Zhao
2026	J	`jnl`	Causal Representation Meets Stochastic Modeling under Generic Geometry. CoRR Jiaxu Ren, Yixin Wang, Biwei Huang
2026	J	`jnl`	DreamSAC: Learning Hamiltonian World Models via Symmetry Exploration. CoRR Jinzhou Tang, Fan Feng, Minghao Fu, Wenjun Lin, Biwei Huang, Keze Wang
2026	J	`jnl`	Factored Causal Representation Learning for Robust Reward Modeling in RLHF. CoRR Yupei Yang, Lin Yang, Wanxi Deng, Lin Qu, Fan Feng, Biwei Huang, Shikui Tu, Lei Xu
2026	J	`jnl`	From Small to Large: In-Context Learning as a New Paradigm for Domain Generalization. Int. J. Comput. Vis. Guanglin Zhou, Zhongyi Han, Shaoan Xie, Shiming Chen, Biwei Huang, Liming Zhu, Xinbo Gao, Lina Yao, Salman H. Khan
2026	J	`jnl`	Hybrid Self-evolving Structured Memory for GUI Agents. CoRR Sibo Zhu, Wenyi Wu, Kun Zhou, Stephen Wang, Biwei Huang
2026	J	`jnl`	Identifying Weight-Variant Latent Causal Models. J. Mach. Learn. Res. Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi
2026	J	`jnl`	Learning Modal-Mixed Chain-of-Thought Reasoning with Latent Embeddings. CoRR Yifei Shao, Kun Zhou, Ziming Xu, Mohammad Atif Quamar, Shibo Hao, Zhen Wang, Zhiting Hu, Biwei Huang
2026	A*	`conf`	Revisiting Differentiable Structure Learning: Inconsistency of L1 Penalty and Beyond. AAAI Kaifeng Jin, Ignavier Ng, Kun Zhang, Biwei Huang
2026	J	`jnl`	ToolGym: an Open-world Tool-using Environment for Scalable Agent Testing and Data Curation. CoRR 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	J	`jnl`	Transformer Is Inherently a Causal Learner. CoRR Xinyue Wang, Stephen Wang, Biwei Huang
2025	J	`jnl`	A Fast Kernel-based Conditional Independence test with Application to Causal Discovery. CoRR Oliver Schacht, Biwei Huang
2025	A*	`conf`	A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery. ICLR Yingyu Lin, Yuxing Huang, Wenqin Liu, Haoran Deng, Ignavier Ng, Kun Zhang, Mingming Gong, Yian Ma, Biwei Huang
2025	J	`jnl`	Activation Control for Efficiently Eliciting Long Chain-of-thought Ability of Language Models. CoRR Zekai Zhao, Qi Liu, Kun Zhou, Zihan Liu, Yifei Shao, Zhiting Hu, Biwei Huang
2025	A*	`conf`	Analytic DAG Constraints for Differentiable DAG Learning. ICLR Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Mingming Gong, Biwei Huang, Kun Zhang, Anton van den Hengel, Javen Qinfeng Shi
2025	J	`jnl`	Analytic DAG Constraints for Differentiable DAG Learning. CoRR Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Mingming Gong, Biwei Huang, Kun Zhang, Anton van den Hengel, Javen Qinfeng Shi
2025	J	`jnl`	Auto-scaling Continuous Memory for GUI Agent. CoRR Wenyi Wu, Kun Zhou, Ruoxin Yuan, Vivian Yu, Stephen Wang, Zhiting Hu, Biwei Huang
2025	J	`jnl`	Backdoor Attribution: Elucidating and Controlling Backdoor in Language Models. CoRR Miao Yu, Zhenhong Zhou, Moayad Aloqaily, Kun Wang, Biwei Huang, Stephen Wang, Yueming Jin, Qingsong Wen
2025	—	`ed.`	Causal Learning and Reasoning, Lausanne, Switzerland, 7-9 May 2025. CLeaR Biwei Huang, Mathias Drton
2025	J	`jnl`	Causal Structure Learning in Hawkes Processes with Complex Latent Confounder Networks. CoRR Songyao Jin, Biwei Huang
2025	J	`jnl`	Causal-Copilot: An Autonomous Causal Analysis Agent. CoRR Xinyue Wang, Kun Zhou, Wenyi Wu, Har Simrat Singh, Fang Nan, Songyao Jin, Aryan Philip, Saloni Patnaik, Hou Zhu, Shivam Singh, Parjanya Prajakta Prashant, Qian Shen, Biwei Huang
2025	J	`jnl`	Causality Meets Locality: Provably Generalizable and Scalable Policy Learning for Networked Systems. CoRR Hao Liang, Shuqing Shi, Yudi Zhang, Biwei Huang, Yali Du
2025	J	`jnl`	DEPTH: Hallucination-Free Relation Extraction via Dependency-Aware Sentence Simplification and Two-tiered Hierarchical Refinement. CoRR Yupei Yang, Fan Feng, Lin Yang, Wanxi Deng, Lin Qu, Biwei Huang, Shikui Tu, Lei Xu
2025	A*	`conf`	Differentiable Causal Discovery for Latent Hierarchical Causal Models. ICLR Parjanya Prajakta Prashant, Ignavier Ng, Kun Zhang, Biwei Huang
2025	J	`jnl`	Gene Regulatory Network Inference in the Presence of Selection Bias and Latent Confounders. CoRR Gongxu Luo, Haoyue Dai, Boyang Sun, Loka Li, Biwei Huang, Petar Stojanov, Kun Zhang
2025	J	`jnl`	HCVP: Leveraging Hierarchical Contrastive Visual Prompt for Domain Generalization. IEEE Trans. Multim. Guanglin Zhou, Zhongyi Han, Shiming Chen, Biwei Huang, Liming Zhu, Tongliang Liu, Lina Yao, Kun Zhang
2025	J	`jnl`	I Predict Therefore I Am: Is Next Token Prediction Enough to Learn Human-Interpretable Concepts from Data? CoRR Yuhang Liu, Dong Gong, Erdun Gao, Zhen Zhang, Biwei Huang, Mingming Gong, Anton van den Hengel, Javen Qinfeng Shi
2025	J	`jnl`	Identification of Nonparametric Dynamic Causal Structure and Latent Process in Climate System. CoRR Minghao Fu, Biwei Huang, Zijian Li, Yujia Zheng, Ignavier Ng, Yingyao Hu, Kun Zhang
2025	J	`jnl`	Latent Covariate Shift: Unlocking Partial Identifiability for Multi-Source Domain Adaptation. Trans. Mach. Learn. Res. Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi
2025	J	`jnl`	Learning Plug-and-play Memory for Guiding Video Diffusion Models. CoRR Selena Song, Ziming Xu, Zijun Zhang, Kun Zhou, Jiaxian Guo, Lianhui Qin, Biwei Huang
2025	J	`jnl`	MACCA: Offline Multi-agent Reinforcement Learning with Causal Credit Assignment. Trans. Mach. Learn. Res. Ziyan Wang, Yali Du, Yudi Zhang, Meng Fang, Biwei Huang
2025	A*	`conf`	MissScore: High-Order Score Estimation in the Presence of Missing Data. ICML Wenqin Liu, Haoze Hou, Erdun Gao, Biwei Huang, Qiuhong Ke, Howard D. Bondell, Mingming Gong
2025	A*	`conf`	Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning. ICLR Xinyue Wang, Biwei Huang
2025	J	`jnl`	Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning. CoRR Xinyue Wang, Biwei Huang
2025	J	`jnl`	Reinforcement Learning for Causal Discovery without Acyclicity Constraints. Trans. Mach. Learn. Res. Bao Duong, Hung Le, Biwei Huang, Thin Nguyen
2025	J	`jnl`	Towards General Continuous Memory for Vision-Language Models. CoRR Wenyi Wu, Zixuan Song, Kun Zhou, Yifei Shao, Zhiting Hu, Biwei Huang
2025	A*	`conf`	Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations. ICLR Yupei Yang, Biwei Huang, Fan Feng, Xinyue Wang, Shikui Tu, Lei Xu
2024	J	`jnl`	A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery. CoRR Yingyu Lin, Yuxing Huang, Wenqin Liu, Haoran Deng, Ignavier Ng, Kun Zhang, Mingming Gong, Yi-An Ma, Biwei Huang
2024	A*	`conf`	A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables. ICLR Xinshuai Dong, Biwei Huang, Ignavier Ng, Xiangchen Song, Yujia Zheng, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
2024	A*	`conf`	ACAMDA: Improving Data Efficiency in Reinforcement Learning through Guided Counterfactual Data Augmentation. AAAI Yuewen Sun, Erli Wang, Biwei Huang, Chaochao Lu, Lu Feng, Changyin Sun, Kun Zhang
2024	J	`jnl`	Adapting Large Multimodal Models to Distribution Shifts: The Role of In-Context Learning. CoRR Guanglin Zhou, Zhongyi Han, Shiming Chen, Biwei Huang, Liming Zhu, Salman Khan, Xinbo Gao, Lina Yao
2024	A*	`conf`	An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series. ICML Qiang Huang, Chuizheng Meng, Defu Cao, Biwei Huang, Yi Chang, Yan Liu
2024	J	`jnl`	An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series. CoRR Qiang Huang, Chuizheng Meng, Defu Cao, Biwei Huang, Yi Chang, Yan Liu
2024	A*	`conf`	Boosting Efficiency in Task-Agnostic Exploration through Causal Knowledge. IJCAI Yupei Yang, Biwei Huang, Shikui Tu, Lei Xu
2024	J	`jnl`	Boosting Efficiency in Task-Agnostic Exploration through Causal Knowledge. CoRR Yupei Yang, Biwei Huang, Shikui Tu, Lei Xu
2024	—	`conf`	Causal Discovery with Mixed Linear and Nonlinear Additive Noise Models: A Scalable Approach. CLeaR Wenqin Liu, Biwei Huang, Erdun Gao, Qiuhong Ke, Howard D. Bondell, Mingming Gong
2024	J	`jnl`	Causal-learn: Causal Discovery in Python. J. Mach. Learn. Res. Yujia Zheng, Biwei Huang, Wei Chen, Joseph D. Ramsey, Mingming Gong, Ruichu Cai, Shohei Shimizu, Peter Spirtes, Kun Zhang
2024	J	`jnl`	Differentiable Causal Discovery For Latent Hierarchical Causal Models. CoRR Parjanya Prajakta Prashant, Ignavier Ng, Kun Zhang, Biwei Huang
2024	A*	`conf`	Federated Causal Discovery from Heterogeneous Data. ICLR Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang
2024	J	`jnl`	Federated Causal Discovery from Heterogeneous Data. CoRR Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang
2024	J	`jnl`	Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables. J. Mach. Learn. Res. Feng Xie, Biwei Huang, Zhengming Chen, Ruichu Cai, Clark Glymour, Zhi Geng, Kun Zhang
2024	J	`jnl`	HCVP: Leveraging Hierarchical Contrastive Visual Prompt for Domain Generalization. CoRR Guanglin Zhou, Zhongyi Han, Shiming Chen, Biwei Huang, Liming Zhu, Tongliang Liu, Lina Yao, Kun Zhang
2024	A*	`conf`	Identifiability Analysis of Linear ODE Systems with Hidden Confounders. NeurIPS Yuanyuan Wang, Biwei Huang, Wei Huang, Xi Geng, Mingming Gong
2024	J	`jnl`	Identifiability Analysis of Linear ODE Systems with Hidden Confounders. CoRR Yuanyuan Wang, Biwei Huang, Wei Huang, Xi Geng, Mingming Gong
2024	J	`jnl`	Identifiable Latent Neural Causal Models. CoRR Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi
2024	A*	`conf`	Identifiable Latent Polynomial Causal Models through the Lens of Change. ICLR Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi
2024	A*	`conf`	Identifying Latent State-Transition Processes for Individualized Reinforcement Learning. NeurIPS Yuewen Sun, Biwei Huang, Yu Yao, Donghuo Zeng, Xinshuai Dong, Songyao Jin, Boyang Sun, Roberto Legaspi, Kazushi Ikeda, Peter Spirtes, Kun Zhang
2024	A*	`conf`	Learning Discrete Concepts in Latent Hierarchical Models. NeurIPS Lingjing Kong, Guangyi Chen, Biwei Huang, Eric P. Xing, Yuejie Chi, Kun Zhang
2024	J	`jnl`	Learning Discrete Concepts in Latent Hierarchical Models. CoRR Lingjing Kong, Guangyi Chen, Biwei Huang, Eric P. Xing, Yuejie Chi, Kun Zhang
2024	A*	`conf`	Natural Counterfactuals With Necessary Backtracking. NeurIPS Guang-Yuan Hao, Jiji Zhang, Biwei Huang, Hao Wang, Kun Zhang
2024	J	`jnl`	Natural Counterfactuals With Necessary Backtracking. CoRR Guang-Yuan Hao, Jiji Zhang, Biwei Huang, Hao Wang, Kun Zhang
2024	A*	`conf`	On Causal Discovery in the Presence of Deterministic Relations. NeurIPS Loka Li, Haoyue Dai, Hanin Al Ghothani, Biwei Huang, Jiji Zhang, Shahar Harel, Isaac Bentwich, Guangyi Chen, Kun Zhang
2024	A*	`conf`	On the Parameter Identifiability of Partially Observed Linear Causal Models. NeurIPS Xinshuai Dong, Ignavier Ng, Biwei Huang, Yuewen Sun, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
2024	J	`jnl`	On the Parameter Identifiability of Partially Observed Linear Causal Models. CoRR Xinshuai Dong, Ignavier Ng, Biwei Huang, Yuewen Sun, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
2024	A*	`conf`	Optimal Kernel Choice for Score Function-based Causal Discovery. ICML Wenjie Wang, Biwei Huang, Feng Liu, Xinge You, Tongliang Liu, Kun Zhang, Mingming Gong
2024	J	`jnl`	Optimal Kernel Choice for Score Function-based Causal Discovery. CoRR Wenjie Wang, Biwei Huang, Feng Liu, Xinge You, Tongliang Liu, Kun Zhang, Mingming Gong
2024	J	`jnl`	Rethinking State Disentanglement in Causal Reinforcement Learning. CoRR Haiyao Cao, Zhen Zhang, Panpan Cai, Yuhang Liu, Jinan Zou, Ehsan Abbasnejad, Biwei Huang, Mingming Gong, Anton van den Hengel, Javen Qinfeng Shi
2024	J	`jnl`	Revealing Multimodal Contrastive Representation Learning through Latent Partial Causal Models. CoRR Yuhang Liu, Zhen Zhang, Dong Gong, Biwei Huang, Mingming Gong, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi
2024	J	`jnl`	Revisiting Differentiable Structure Learning: Inconsistency of ℓ CoRR Kaifeng Jin, Ignavier Ng, Kun Zhang, Biwei Huang
2024	A*	`conf`	Score-Based Causal Discovery of Latent Variable Causal Models. ICML Ignavier Ng, Xinshuai Dong, Haoyue Dai, Biwei Huang, Peter Spirtes, Kun Zhang
2024	A*	`conf`	Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability. ICLR Songyao Jin, Feng Xie, Guangyi Chen, Biwei Huang, Zhengming Chen, Xinshuai Dong, Kun Zhang
2024	—	`conf`	Structure Learning with Continuous Optimization: A Sober Look and Beyond. CLeaR Ignavier Ng, Biwei Huang, Kun Zhang
2024	J	`jnl`	Testability of Instrumental Variables in Additive Nonlinear, Non-Constant Effects Models. CoRR Xichen Guo, Zheng Li, Biwei Huang, Yan Zeng, Zhi Geng, Feng Xie
2023	J	`jnl`	A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables. CoRR Xinshuai Dong, Biwei Huang, Ignavier Ng, Xiangchen Song, Yujia Zheng, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
2023	J	`jnl`	Advancing Counterfactual Inference through Quantile Regression. CoRR Shaoan Xie, Biwei Huang, Bin Gu, Tongliang Liu, Kun Zhang
2023	J	`jnl`	Causal-learn: Causal Discovery in Python. CoRR Yujia Zheng, Biwei Huang, Wei Chen, Joseph D. Ramsey, Mingming Gong, Ruichu Cai, Shohei Shimizu, Peter Spirtes, Kun Zhang
2023	J	`jnl`	GRD: A Generative Approach for Interpretable Reward Redistribution in Reinforcement Learning. CoRR Yudi Zhang, Yali Du, Biwei Huang, Ziyan Wang, Jun Wang, Meng Fang, Mykola Pechenizkiy
2023	J	`jnl`	Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables. CoRR Feng Xie, Biwei Huang, Zhengming Chen, Ruichu Cai, Clark Glymour, Zhi Geng, Kun Zhang
2023	A*	`conf`	Generator Identification for Linear SDEs with Additive and Multiplicative Noise. NeurIPS Yuanyuan Wang, Xi Geng, Wei Huang, Biwei Huang, Mingming Gong
2023	J	`jnl`	Generator Identification for Linear SDEs with Additive and Multiplicative Noise. CoRR Yuanyuan Wang, Xi Geng, Wei Huang, Biwei Huang, Mingming Gong
2023	J	`jnl`	Identifiable Latent Polynomial Causal Models Through the Lens of Change. CoRR Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi
2023	A*	`conf`	Identification of Nonlinear Latent Hierarchical Models. NeurIPS Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang
2023	J	`jnl`	Identification of Nonlinear Latent Hierarchical Models. CoRR Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang
2023	A*	`conf`	Interpretable Reward Redistribution in Reinforcement Learning: A Causal Approach. NeurIPS Yudi Zhang, Yali Du, Biwei Huang, Ziyan Wang, Jun Wang, Meng Fang, Mykola Pechenizkiy
2023	A*	`conf`	Learning World Models with Identifiable Factorization. NeurIPS Yuren Liu, Biwei Huang, Zhengmao Zhu, Hong-Long Tian, Mingming Gong, Yang Yu, Kun Zhang
2023	J	`jnl`	Learning World Models with Identifiable Factorization. CoRR Yu-Ren Liu, Biwei Huang, Zheng-Mao Zhu, Hong-Long Tian, Mingming Gong, Yang Yu, Kun Zhang
2023	—	`—`	Learning and Using Causal Knowledge: A Further Step Towards a Higher-Level Intelligence Biwei Huang
2023	J	`jnl`	MACCA: Offline Multi-agent Reinforcement Learning with Causal Credit Assignment. CoRR Ziyan Wang, Yali Du, Yudi Zhang, Meng Fang, Biwei Huang
2023	J	`jnl`	Structure Learning with Continuous Optimization: A Sober Look and Beyond. CoRR Ignavier Ng, Biwei Huang, Kun Zhang
2022	A*	`conf`	Action-Sufficient State Representation Learning for Control with Structural Constraints. ICML Biwei Huang, Chaochao Lu, Liu Leqi, José Miguel Hernández-Lobato, Clark Glymour, Bernhard Schölkopf, Kun Zhang
2022	A*	`conf`	AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning. ICLR Biwei Huang, Fan Feng, Chaochao Lu, Sara Magliacane, Kun Zhang
2022	A*	`conf`	Factored Adaptation for Non-Stationary Reinforcement Learning. NeurIPS Fan Feng, Biwei Huang, Kun Zhang, Sara Magliacane
2022	J	`jnl`	Factored Adaptation for Non-Stationary Reinforcement Learning. CoRR Fan Feng, Biwei Huang, Kun Zhang, Sara Magliacane
2022	A*	`conf`	Identification of Linear Non-Gaussian Latent Hierarchical Structure. ICML Feng Xie, Biwei Huang, Zhengming Chen, Yangbo He, Zhi Geng, Kun Zhang
2022	J	`jnl`	Identifying Latent Causal Content for Multi-Source Domain Adaptation. CoRR Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Kun Zhang, Javen Qinfeng Shi
2022	A*	`conf`	Latent Hierarchical Causal Structure Discovery with Rank Constraints. NeurIPS Biwei Huang, Charles Jia Han Low, Feng Xie, Clark Glymour, Kun Zhang
2022	J	`jnl`	Latent Hierarchical Causal Structure Discovery with Rank Constraints. CoRR Biwei Huang, Charles Jia Han Low, Feng Xie, Clark Glymour, Kun Zhang
2022	J	`jnl`	Weight-variant Latent Causal Models. CoRR Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi
2021	J	`jnl`	Action-Sufficient State Representation Learning for Control with Structural Constraints. CoRR Biwei Huang, Chaochao Lu, Liu Leqi, José Miguel Hernández-Lobato, Clark Glymour, Bernhard Schölkopf, Kun Zhang
2021	J	`jnl`	AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning. CoRR Biwei Huang, Fan Feng, Chaochao Lu, Sara Magliacane, Kun Zhang
2021	A*	`conf`	DeepTrader: A Deep Reinforcement Learning Approach for Risk-Return Balanced Portfolio Management with Market Conditions Embedding. AAAI Zhicheng Wang, Biwei Huang, Shikui Tu, Kun Zhang, Lei Xu
2021	J	`jnl`	FRITL: A Hybrid Method for Causal Discovery in the Presence of Latent Confounders. CoRR Wei Chen, Kun Zhang, Ruichu Cai, Biwei Huang, Joseph D. Ramsey, Zhifeng Hao, Clark Glymour
2020	J	`jnl`	Causal Discovery from Heterogeneous/Nonstationary Data. J. Mach. Learn. Res. Biwei Huang, Kun Zhang, Jiji Zhang, Joseph D. Ramsey, Ruben Sanchez-Romero, Clark Glymour, Bernhard Schölkopf
2020	A*	`conf`	Causal Discovery from Multiple Data Sets with Non-Identical Variable Sets. AAAI Biwei Huang, Kun Zhang, Mingming Gong, Clark Glymour
2020	J	`jnl`	Domain Adaptation As a Problem of Inference on Graphical Models. CoRR Kun Zhang, Mingming Gong, Petar Stojanov, Biwei Huang, Clark Glymour
2020	A*	`conf`	Domain Adaptation as a Problem of Inference on Graphical Models. NeurIPS Kun Zhang, Mingming Gong, Petar Stojanov, Biwei Huang, Qingsong Liu, Clark Glymour
2020	A*	`conf`	Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs. NeurIPS Feng Xie, Ruichu Cai, Biwei Huang, Clark Glymour, Zhifeng Hao, Kun Zhang
2020	J	`jnl`	Generalized Independent Noise Condition for Estimating Linear Non-Gaussian Latent Variable Graphs. CoRR Feng Xie, Ruichu Cai, Biwei Huang, Clark Glymour, Zhifeng Hao, Kun Zhang
2020	J	`jnl`	Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation. CoRR Chaochao Lu, Biwei Huang, Ke Wang, José Miguel Hernández-Lobato, Kun Zhang, Bernhard Schölkopf
2019	A*	`conf`	Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models. ICML Biwei Huang, Kun Zhang, Mingming Gong, Clark Glymour
2019	J	`jnl`	Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models. CoRR Biwei Huang, Kun Zhang, Mingming Gong, Clark Glymour
2019	J	`jnl`	Causal Discovery from Heterogeneous/Nonstationary Data. CoRR Biwei Huang, Kun Zhang, Jiji Zhang, Joseph D. Ramsey, Ruben Sanchez-Romero, Clark Glymour, Bernhard Schölkopf
2019	J	`jnl`	Diagnosis of Autism Spectrum Disorder by Causal Influence Strength Learned from Resting-State fMRI Data. CoRR Biwei Huang, Kun Zhang, Ruben Sanchez-Romero, Joseph D. Ramsey, Madelyn Glymour, Clark Glymour
2019	A*	`conf`	Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering. NeurIPS Biwei Huang, Kun Zhang, Pengtao Xie, Mingming Gong, Eric P. Xing, Clark Glymour
2018	J	`jnl`	Causal Generative Domain Adaptation Networks. CoRR Mingming Gong, Kun Zhang, Biwei Huang, Clark Glymour, Dacheng Tao, Kayhan Batmanghelich
2018	A*	`conf`	Generalized Score Functions for Causal Discovery. KDD Biwei Huang, Kun Zhang, Yizhu Lin, Bernhard Schölkopf, Clark Glymour
2018	A*	`conf`	Multi-domain Causal Structure Learning in Linear Systems. NeurIPS AmirEmad Ghassami, Negar Kiyavash, Biwei Huang, Kun Zhang
2017	A*	`conf`	Behind Distribution Shift: Mining Driving Forces of Changes and Causal Arrows. ICDM Biwei Huang, Kun Zhang, Jiji Zhang, Ruben Sanchez-Romero, Clark Glymour, Bernhard Schölkopf
2017	A*	`conf`	Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination. IJCAI Kun Zhang, Biwei Huang, Jiji Zhang, Clark Glymour, Bernhard Schölkopf
2016	A	`conf`	On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection. UAI Kun Zhang, Jiji Zhang, Biwei Huang, Bernhard Schölkopf, Clark Glymour
2015	A*	`conf`	Identification of Time-Dependent Causal Model: A Gaussian Process Treatment. IJCAI Biwei Huang, Kun Zhang, Bernhard Schölkopf
2015	J	`jnl`	Towards Robust and Specific Causal Discovery from fMRI. CoRR Kun Zhang, Biwei Huang, Bernhard Schölkopf, Michel Besserve, Masataka Watanabe, Dajiang Zhu