Kun Zhang

发表

Identification of Partially Observed Linear Causal Models: Graphical Conditions for the Non-Gaussian and Heterogeneous Cases

N. Hansen, Jeffrey Adams, Kun Zhang, 2021, NeurIPS.

Identifying Latent Causal Content for Multi-Source Domain Adaptation

Mingming Gong, Biwei Huang, J. Shi, 2022, ArXiv.

Weight-variant Latent Causal Models

A. V. Hengel, Mingming Gong, Dong Gong, 2022, ArXiv.

Identifying Weight-Variant Latent Causal Models

A. V. Hengel, Mingming Gong, Biwei Huang, 2022, 2208.14153.

Identifying Latent Causal Content for Multi-Source Domain Adaptation

Mingming Gong, Biwei Huang, J. Shi, 2022, ArXiv.

Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models

P. Spirtes, Kun Zhang, Haoyue Dai, 2022, Neural Information Processing Systems.

Supplementary Material: Identiﬁcation of Partially Observed Linear Causal Models

N. Hansen, Jeffrey Adams, Kun Zhang, 2022 .

Latent Hierarchical Causal Structure Discovery with Rank Constraints

C. Glymour, Biwei Huang, Feng Xie, 2022, NeurIPS.

Causal Inference

Z. Geng, P. Ding, Zhichao Jiang, 2020, Engineering.

On the Opportunity of Causal Deep Generative Models: A Survey and Future Directions

Xiwei Xu, Guanglin Zhou, Kun Zhang, 2023, ArXiv.

Identification of Linear Non-Gaussian Latent Hierarchical Structure

Yangbo He, Z. Geng, Biwei Huang, 2022, ICML.

Structure Learning with Continuous Optimization: A Sober Look and Beyond

Biwei Huang, Ignavier Ng, Kun Zhang, 2023, CLeaR.

DeepTrader: A Deep Reinforcement Learning Approach for Risk-Return Balanced Portfolio Management with Market Conditions Embedding

Lei Xu, Shikui Tu, Biwei Huang, 2021, AAAI.

Scalable Causal Discovery with Score Matching

L. Rosasco, Francesco Locatello, Nicoletta Noceti, 2023, CLeaR.

Identification of Nonlinear Latent Hierarchical Models

E. Xing, Yuejie Chi, Biwei Huang, 2023, ArXiv.

Learning World Models with Identifiable Factorization

Mingming Gong, Biwei Huang, Yang Yu, 2023, NeurIPS.

Advances in Causal Representation Learning: Discovery of the Hidden World

Kun Zhang, 2023 .

Causal Discovery with Score Matching on Additive Models with Arbitrary Noise

L. Rosasco, Francesco Locatello, Nicoletta Noceti, 2023, CLeaR.

Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks

Ignavier Ng, Yewen Fan, Kun Zhang, 2023, International Conference on Learning Representations.

Advancing Counterfactual Inference through Quantile Regression

Shaoan Xie, Biwei Huang, Kun Zhang, 2023, ArXiv.

Identifying Weight-Variant Latent Causal Models

Mingming Gong, Biwei Huang, Kun Zhang, 2022, 2208.14153.

Emerging Synergies in Causality and Deep Generative Models: A Survey

Shaoan Xie, Xiwei Xu, Biwei Huang, 2023, 2301.12351.

Causal Discovery with Latent Confounders Based on Higher-Order Cumulants

Z. Hao, W. Chen, Ruichu Cai, 2023, ICML.

Emerging Synergies in Causality and Deep Generative Models: A Survey

Shaoan Xie, Xiwei Xu, Biwei Huang, 2023, 2301.12351.

A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables

P. Spirtes, Biwei Huang, Ignavier Ng, 2023, ArXiv.

Identification of Nonlinear Latent Hierarchical Models

E. Xing, Yuejie Chi, Biwei Huang, 2023, NeurIPS.

Causal discovery of 1-factor measurement models in linear latent variable models with arbitrary noise distributions

Yangbo He, Zhen Chen, Yan Zeng, 2023, Neurocomputing.

Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables

C. Glymour, Biwei Huang, Zhen Chen, 2023, ArXiv.

Identifying Weight-Variant Latent Causal Models

Mingming Gong, Biwei Huang, Kun Zhang, 2022, 2208.14153.