Kun Zhang

ORCID

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 245

Top Venues

Chinese University of Hong Kong, Hong Kong (PHD)

Education History

Chinese University of Hong Kong, Hong Kong

PHD

Publications

Cheng Xu, Keke Li, Xuandi Luo, Xuemiao Xu, Shengfeng He, Kun Zhang
Fully Deformable Network for Multiview Face Image Synthesis. IEEE Trans. Neural Networks Learn. Syst. 35 (7) (2024)
Ignavier Ng, Biwei Huang, Kun Zhang
Structure Learning with Continuous Optimization: A Sober Look and Beyond. CLeaR (2024)
Lingjing Kong, Guangyi Chen, Biwei Huang, Eric P. Xing, Yuejie Chi, Kun Zhang
Learning Discrete Concepts in Latent Hierarchical Models. CoRR (2024)
Zijian Li, Yifan Shen, Kaitao Zheng, Ruichu Cai, Xiangchen Song, Mingming Gong, Zhifeng Hao, Zhengmao Zhu, Guangyi Chen, Kun Zhang
On the Identification of Temporally Causal Representation with Instantaneous Dependence. CoRR (2024)
Ruichu Cai, Zhifang Jiang, Zijian Li, Weilin Chen, Xuexin Chen, Zhifeng Hao, Yifan Shen, Guangyi Chen, Kun Zhang
From Orthogonality to Dependency: Learning Disentangled Representation for Multi-Modal Time-Series Sensing Signals. CoRR (2024)
Yuqin Yang, Mohamed S. Nafea, Negar Kiyavash, Kun Zhang, AmirEmad Ghassami
Causal Discovery in Linear Models with Unobserved Variables and Measurement Error. CoRR (2024)
Zeyu Tang, Jialu Wang, Yang Liu, Peter Spirtes, Kun Zhang
Procedural Fairness Through Decoupling Objectionable Data Generating Components. ICLR (2024)
Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi
Identifiable Latent Neural Causal Models. CoRR (2024)
Yuewen Sun, Erli Wang, Biwei Huang, Chaochao Lu, Lu Feng, Changyin Sun, Kun Zhang
ACAMDA: Improving Data Efficiency in Reinforcement Learning through Guided Counterfactual Data Augmentation. AAAI (2024)
Xinshuai Dong, Ignavier Ng, Biwei Huang, Yuewen Sun, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
On the Parameter Identifiability of Partially Observed Linear Causal Models. CoRR (2024)
Yujia Zheng, Zeyu Tang, Yiwen Qiu, Bernhard Schölkopf, Kun Zhang
Detecting and Identifying Selection Structure in Sequential Data. CoRR (2024)
Xinshuai Dong, Biwei Huang, Ignavier Ng, Xiangchen Song, Yujia Zheng, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables. ICLR (2024)
Shunxing Fan, Mingming Gong, Kun Zhang
On the Recoverability of Causal Relations from Temporally Aggregated I.I.D. Data. CoRR (2024)
Yewen Fan, Nian Si, Xiangchen Song, Kun Zhang
Calibration-then-Calculation: A Variance Reduced Metric Framework in Deep Click-Through Rate Prediction Models. CoRR (2024)
Hanqi Yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric P. Xing, Yulan He, Kun Zhang
Counterfactual Generation with Identifiability Guarantees. CoRR (2024)
Longkang Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang
Federated Causal Discovery from Heterogeneous Data. ICLR (2024)
Usman Gohar, Zeyu Tang, Jialu Wang, Kun Zhang, Peter L. Spirtes, Yang Liu, Lu Cheng
Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges. CoRR (2024)
Sheng Zhang, Muzammal Naseer, Guangyi Chen, Zhiqiang Shen, Salman H. Khan, Kun Zhang, Fahad Shahbaz Khan
S3A: Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment. AAAI (2024)
Kun Zhang, Ilya Shpitser, Sara Magliacane, Davide Bacciu, Fei Wu, Changshui Zhang, Peter Spirtes
IEEE Transactions on Neural Networks and Learning Systems Special Issue on Causal Discovery and Causality-Inspired Machine Learning. IEEE Trans. Neural Networks Learn. Syst. 35 (4) (2024)
Zhengming Chen, Ruichu Cai, Feng Xie, Jie Qiao, Anpeng Wu, Zijian Li, Zhifeng Hao, Kun Zhang
Learning Discrete Latent Variable Structures with Tensor Rank Conditions. CoRR (2024)
Tianjun Yao, Yongqiang Chen, Zhenhao Chen, Kai Hu, Zhiqiang Shen, Kun Zhang
Empowering Graph Invariance Learning with Deep Spurious Infomax. CoRR (2024)
Charvi Rastogi, Xiangchen Song, Zhijing Jin, Ivan Stelmakh, Hal Daumé III, Kun Zhang, Nihar B. Shah
A Randomized Controlled Trial on Anonymizing Reviewers to Each Other in Peer Review Discussions. CoRR (2024)
Yue Cong, Jing Qiu, Kun Zhang, Zhongyang Fang, Chengliang Gao, Shen Su, Zhihong Tian
Ada-FFL: Adaptive computing fairness federated learning. CAAI Trans. Intell. Technol. 9 (3) (2024)
Wei Chen, Zhiyi Huang, Ruichu Cai, Zhifeng Hao, Kun Zhang
Identification of Causal Structure with Latent Variables Based on Higher Order Cumulants. AAAI (2024)
Haoyue Dai, Ignavier Ng, Gongxu Luo, Peter Spirtes, Petar Stojanov, Kun Zhang
Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View. ICLR (2024)
Donghuo Zeng, Roberto Legaspi, Yuewen Sun, Xinshuai Dong, Kazushi Ikeda, Peter Spirtes, Kun Zhang
Counterfactual Reasoning Using Predicted Latent Personality Dimensions for Optimizing Persuasion Outcome. CoRR (2024)
Jingling Li, Zeyu Tang, Xiaoyu Liu, Peter Spirtes, Kun Zhang, Liu Leqi, Yang Liu
Steering LLMs Towards Unbiased Responses: A Causality-Guided Debiasing Framework. CoRR (2024)
Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang
Federated Causal Discovery from Heterogeneous Data. CoRR (2024)
Xinshuai Dong, Haoyue Dai, Yewen Fan, Songyao Jin, Sathyamoorthy Rajendran, Kun Zhang
On the Three Demons in Causality in Finance: Time Resolution, Nonstationarity, and Latent Factors. CoRR (2024)
Songyao Jin, Feng Xie, Guangyi Chen, Biwei Huang, Zhengming Chen, Xinshuai Dong, Kun Zhang
Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability. ICLR (2024)
Haoyue Dai, Ignavier Ng, Yujia Zheng, Zhengqing Gao, Kun Zhang
Local Causal Discovery with Linear non-Gaussian Cyclic Models. CoRR (2024)
Tianjun Yao, Jiaqi Sun, Defu Cao, Kun Zhang, Guangyi Chen
MuGSI: Distilling GNNs with Multi-Granularity Structural Information for Graph Classification. WWW (2024)
Xiu-Chuan Li, Kun Zhang, Tongliang Liu
Causal Structure Recovery with Latent Variables under Milder Distributional and Graphical Assumptions. ICLR (2024)
Donghuo Zeng, Roberto Sebastian Legaspi, Yuewen Sun, Xinshuai Dong, Kazushi Ikeda, Peter Spirtes, Kun Zhang
Counterfactual Reasoning Using Predicted Latent Personality Dimensions for Optimizing Persuasion Outcome. PERSUASIVE (2024)
Ruichu Cai, Fengzhu Wu, Zijian Li, Pengfei Wei, Lingling Yi, Kun Zhang
Graph Domain Adaptation: A Generative View. ACM Trans. Knowl. Discov. Data 18 (3) (2024)
Guangyi Chen, Yuke Li, Xiao Liu, Zijian Li, Eman Al Suradi, Donglai Wei, Kun Zhang
LLCP: Learning Latent Causal Processes for Reasoning-based Video Question Answer. ICLR (2024)
Haoyue Dai, Ignavier Ng, Yujia Zheng, Zhengqing Gao, Kun Zhang
Local Causal Discovery with Linear non-Gaussian Cyclic Models. AISTATS (2024)
Hanqi Yan, Lin Gui, Menghan Wang, Kun Zhang, Yulan He
Explainable Recommender With Geometric Information Bottleneck. IEEE Trans. Knowl. Data Eng. 36 (7) (2024)
Weiwei Cai, Xuemiao Xu, Jiajia Xu, Huaidong Zhang, Haoxin Yang, Kun Zhang, Shengfeng He
Hierarchical damage correlations for old photo restoration. Inf. Fusion 107 (2024)
Guangyi Chen, Yifan Shen, Zhenhao Chen, Xiangchen Song, Yuewen Sun, Weiran Yao, Xiao Liu, Kun Zhang
CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process. CoRR (2024)
Kun Zhang, Shaoan Xie, Ignavier Ng, Yujia Zheng
Causal Representation Learning from Multiple Distributions: A General Setting. CoRR (2024)
Tianjun Yao, Jiaqi Sun, Defu Cao, Kun Zhang, Guangyi Chen
MuGSI: Distilling GNNs with Multi-Granularity Structural Information for Graph Classification. CoRR (2024)
Guanglin Zhou, Zhongyi Han, Shiming Chen, Biwei Huang, Liming Zhu, Tongliang Liu, Lina Yao, Kun Zhang
HCVP: Leveraging Hierarchical Contrastive Visual Prompt for Domain Generalization. CoRR (2024)
Loka Li, Guangyi Chen, Yusheng Su, Zhenhao Chen, Yixuan Zhang, Eric P. Xing, Kun Zhang
Confidence Matters: Revisiting Intrinsic Self-Correction Capabilities of Large Language Models. CoRR (2024)
Zijian Li, Ruichu Cai, Tom Z. J. Fu, Zhifeng Hao, Kun Zhang
Transferable Time-Series Forecasting Under Causal Conditional Shift. IEEE Trans. Pattern Anal. Mach. Intell. 46 (4) (2024)
Haoyue Dai, Ignavier Ng, Gongxu Luo, Peter Spirtes, Petar Stojanov, Kun Zhang
Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View. CoRR (2024)
Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi
Identifiable Latent Polynomial Causal Models through the Lens of Change. ICLR (2024)
Zijian Li, Ruichu Cai, Zhenhui Yang, Haiqin Huang, Guangyi Chen, Yifan Shen, Zhengming Chen, Xiangchen Song, Zhifeng Hao, Kun Zhang
When and How: Learning Identifiable Latent States for Nonstationary Time Series Forecasting. CoRR (2024)
Wenjie Wang, Biwei Huang, Feng Liu, Xinge You, Tongliang Liu, Kun Zhang, Mingming Gong
Optimal Kernel Choice for Score Function-based Causal Discovery. CoRR (2024)
Shaoan Xie, Yang Zhao, Zhisheng Xiao, Kelvin C. K. Chan, Yandong Li, Yanwu Xu, Kun Zhang, Tingbo Hou
DreamInpainter: Text-Guided Subject-Driven Image Inpainting with Diffusion Models. CoRR (2023)
Feng Xie, Biwei Huang, Zhengming Chen, Ruichu Cai, Clark Glymour, Zhi Geng, Kun Zhang
Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables. CoRR (2023)
Ignavier Ng, Biwei Huang, Kun Zhang
Structure Learning with Continuous Optimization: A Sober Look and Beyond. CoRR (2023)
Tianjun Yao, Yingxu Wang, Kun Zhang, Shangsong Liang
Improving the Expressiveness of K-hop Message-Passing GNNs by Injecting Contextualized Substructure Information. KDD (2023)
Negar Kiyavash, Elias Bareinboim, Todd P. Coleman, Alex Dimakis, Bernhard Schlkopf, Peter Spirtes, Kun Zhang, Robert Nowak
Editorial Special Issue on Causality: Fundamental Limits and Applications. IEEE J. Sel. Areas Inf. Theory 4 (2023)
Ruichu Cai, Zhiyi Huang, Wei Chen, Zhifeng Hao, Kun Zhang
Causal Discovery with Latent Confounders Based on Higher-Order Cumulants. ICML (2023)
Lingjing Kong, Martin Q. Ma, Guangyi Chen, Eric P. Xing, Yuejie Chi, Louis-Philippe Morency, Kun Zhang
Understanding Masked Autoencoders via Hierarchical Latent Variable Models. CoRR (2023)
Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello
Scalable Causal Discovery with Score Matching. CLeaR (2023)
Yuren Liu, Biwei Huang, Zhengmao Zhu, Hong-Long Tian, Mingming Gong, Yang Yu, Kun Zhang
Learning World Models with Identifiable Factorization. NeurIPS (2023)
Weiwei Cai, Huaidong Zhang, Xuemiao Xu, Shengfeng He, Kun Zhang, Jing Qin
Contextual-Assisted Scratched Photo Restoration. IEEE Trans. Circuits Syst. Video Technol. 33 (10) (2023)
Ruichu Cai, Zhiyi Huang, Wei Chen, Zhifeng Hao, Kun Zhang
Causal Discovery with Latent Confounders Based on Higher-Order Cumulants. CoRR (2023)
Yewen Fan, Nian Si, Kun Zhang
Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems. ICLR (2023)
Zijian Li, Zunhong Xu, Ruichu Cai, Zhenhui Yang, Yuguang Yan, Zhifeng Hao, Guangyi Chen, Kun Zhang
Identifying Semantic Component for Robust Molecular Property Prediction. CoRR (2023)
Zijian Li, Ruichu Cai, Guangyi Chen, Boyang Sun, Zhifeng Hao, Kun Zhang
Subspace Identification for Multi-Source Domain Adaptation. CoRR (2023)
Ignavier Ng, Yujia Zheng, Xinshuai Dong, Kun Zhang
On the Identifiability of Sparse ICA without Assuming Non-Gaussianity. NeurIPS (2023)
Zeyu Tang, Jiji Zhang, Kun Zhang
What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspective. ACM Comput. Surv. 55 (13s) (2023)
Shaoan Xie, Lingjing Kong, Mingming Gong, Kun Zhang
Multi-domain image generation and translation with identifiability guarantees. ICLR (2023)
Junlong Li, Guangyi Chen, Yansong Tang, Jinan Bao, Kun Zhang, Jie Zhou, Jiwen Lu
GAIN: On the Generalization of Instructional Action Understanding. ICLR (2023)
Xinshuai Dong, Biwei Huang, Ignavier Ng, Xiangchen Song, Yujia Zheng, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables. CoRR (2023)
Zeyu Tang, Yatong Chen, Yang Liu, Kun Zhang
Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors. ICLR (2023)
Xinyi Wang, Michael Saxon, Jiachen Li, Hongyang Zhang, Kun Zhang, William Yang Wang
Causal Balancing for Domain Generalization. ICLR (2023)
Wei Chen, Zhiyi Huang, Ruichu Cai, Zhifeng Hao, Kun Zhang
Identification of Causal Structure with Latent Variables Based on Higher Order Cumulants. CoRR (2023)
Zeyu Tang, Jialu Wang, Yang Liu, Peter Spirtes, Kun Zhang
Procedural Fairness Through Decoupling Objectionable Data Generating Components. CoRR (2023)
Xiangchen Song, Weiran Yao, Yewen Fan, Xinshuai Dong, Guangyi Chen, Juan Carlos Niebles, Eric Xing, Kun Zhang
Temporally Disentangled Representation Learning under Unknown Nonstationarity. CoRR (2023)
Hanqi Yan, Lin Gui, Menghan Wang, Kun Zhang, Yulan He
Explainable Recommender with Geometric Information Bottleneck. CoRR (2023)
Mugariya Farooq, Shahad Hardan, Aigerim Zhumbhayeva, Yujia Zheng, Preslav Nakov, Kun Zhang
Understanding Breast Cancer Survival: Using Causality and Language Models on Multi-omics Data. CoRR (2023)
Yu-Ren Liu, Biwei Huang, Zheng-Mao Zhu, Hong-Long Tian, Mingming Gong, Yang Yu, Kun Zhang
Learning World Models with Identifiable Factorization. CoRR (2023)
Zeyu Tang, Yatong Chen, Yang Liu, Kun Zhang
Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors. CoRR (2023)
Lingjing Kong, Martin Q. Ma, Guangyi Chen, Eric P. Xing, Yuejie Chi, Louis-Philippe Morency, Kun Zhang
Understanding Masked Autoencoders via Hierarchical Latent Variable Models. CVPR (2023)
Yujia Zheng, Ignavier Ng, Yewen Fan, Kun Zhang
Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks. ICLR (2023)
Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang
Identification of Nonlinear Latent Hierarchical Models. CoRR (2023)
Yujia Zheng, Biwei Huang, Wei Chen, Joseph D. Ramsey, Mingming Gong, Ruichu Cai, Shohei Shimizu, Peter Spirtes, Kun Zhang
Causal-learn: Causal Discovery in Python. CoRR (2023)
Hao Zhang, Yewei Xia, Kun Zhang, Shuigeng Zhou, Jihong Guan
Conditional Independence Test Based on Residual Similarity. ACM Trans. Knowl. Discov. Data 17 (8) (2023)
Yujia Zheng, Kun Zhang
Generalizing Nonlinear ICA Beyond Structural Sparsity. CoRR (2023)
Yu Yao, Mingming Gong, Yuxuan Du, Jun Yu, Bo Han, Kun Zhang, Tongliang Liu
Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise? ICML (2023)
Shaoan Xie, Yanwu Xu, Mingming Gong, Kun Zhang
Unpaired Image-to-Image Translation with Shortest Path Regularization. CVPR (2023)
Hanqi Yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric P. Xing, Yulan He, Kun Zhang
Counterfactual Generation with Identifiability Guarantees. NeurIPS (2023)
Zijian Li, Ruichu Cai, Guangyi Chen, Boyang Sun, Zhifeng Hao, Kun Zhang
Subspace Identification for Multi-Source Domain Adaptation. NeurIPS (2023)
Yuewen Sun, Kun Zhang, Changyin Sun
Model-Based Transfer Reinforcement Learning Based on Graphical Model Representations. IEEE Trans. Neural Networks Learn. Syst. 34 (2) (2023)
Guangyi Chen, Xiao Liu, Guangrun Wang, Kun Zhang, Philip H. S. Torr, Xiao-Ping Zhang, Yansong Tang
Tem-adapter: Adapting Image-Text Pretraining for Video Question Answer. ICCV (2023)
Xiangchen Song, Weiran Yao, Yewen Fan, Xinshuai Dong, Guangyi Chen, Juan Carlos Niebles, Eric Xing, Kun Zhang
Temporally Disentangled Representation Learning under Unknown Nonstationarity. NeurIPS (2023)
Guangyi Chen, Weiran Yao, Xiangchen Song, Xinyue Li, Yongming Rao, Kun Zhang
PLOT: Prompt Learning with Optimal Transport for Vision-Language Models. ICLR (2023)
Shaoan Xie, Biwei Huang, Bin Gu, Tongliang Liu, Kun Zhang
Advancing Counterfactual Inference through Quantile Regression. CoRR (2023)
Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang
Identification of Nonlinear Latent Hierarchical Models. NeurIPS (2023)
Shaoan Xie, Zhifei Zhang, Zhe Lin, Tobias Hinz, Kun Zhang
SmartBrush: Text and Shape Guided Object Inpainting with Diffusion Model. CVPR (2023)
Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello
Causal Discovery with Score Matching on Additive Models with Arbitrary Noise. CLeaR (2023)
Lingjing Kong, Shaoan Xie, Weiran Yao, Yujia Zheng, Guangyi Chen, Petar Stojanov, Victor Akinwande, Kun Zhang
Partial Identifiability for Domain Adaptation. CoRR (2023)
Yue Yu, Xuan Kan, Hejie Cui, Ran Xu, Yujia Zheng, Xiangchen Song, Yanqiao Zhu, Kun Zhang, Razieh Nabi, Ying Guo, Chao Zhang, Carl Yang
Deep Dag Learning of Effective Brain Connectivity for FMRI Analysis. ISBI (2023)
Zhengming Chen, Feng Xie, Jie Qiao, Zhifeng Hao, Kun Zhang, Ruichu Cai
Identification of Linear Latent Variable Model with Arbitrary Distribution. AAAI (2022)
Yujia Zheng, Ignavier Ng, Kun Zhang
On the Identifiability of Nonlinear ICA: Sparsity and Beyond. CoRR (2022)
Haoyue Dai, Peter Spirtes, Kun Zhang
Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models. CoRR (2022)

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Publication Activity (10 Years)

Top Topics

Top Venues

Kun Zhang