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ORCIDKun Zhang 0001
Person information
- affiliation: Carnegie Mellon University, Department of Philosophy, Pittsburgh, PA, USA
- affiliation: Max Planck Institute for Intelligent Systems, Tübingen, Germany
- affiliation (PhD 2005): Chinese University of Hong Kong, Hong Kong
Other persons with the same name
- Kun Zhang — disambiguation page
- Kun Zhang 0002
![[0000-0002-3543-0137]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0002-3543-0137")
— Taiyuan University of Technology, College of Mechanical Engineering, China - Kun Zhang 0003 — East China Normal University, Key Laboratory of Geographic Information Science, Shanghai, China
- Kun Zhang 0004 — State University of New York at Stony Brook, Department of Physics and Astronomy, NY, USA
- Kun Zhang 0005 — Northeastern University, College of Information Science and Engineering, Shenyang, China
- Kun Zhang 0006 — Georgia Institute of Technology, Atlanta, GA, USA
- Kun Zhang 0007 — Beijing University of Technology, Key Laboratory of Advanced Manufacturing Technology, China
- Kun Zhang 0008 — Air Force Engineering University, Information and Navigation College, Xian, China
- Kun Zhang 0009 — Xidian University, National Laboratory of Radar Signal Processing, China
- Kun Zhang 0010 — Nantong University, School of Electrical Engineering, China
- Kun Zhang 0011 — Hainan University, State Key Laboratory of Marine Resource Utilization in South China Sea, Haikou, China
- Kun Zhang 0012 — Xavier University of Louisiana, New Orleans, LA, USA
- Kun Zhang 0013 — Shandong University, Jinan, China (and 1 more)
- Kun Zhang 0014 — University of Colorado at Boulder, Boulder, CO, USA
- Kun Zhang 0015 — Hefei University of Technology, School of Computer Science and Information Engineering, Key Laboratory of Knowledge Engineering with Big Data, Hefei, China (and 1 more)
- Kun Zhang 0016 — University of Chinese Academy of Sciences, School of Cyber Security, Beijing, China
- Kun Zhang 0017 — Hong Kong University of Science and Technology, Hong Kong (and 1 more)
- Kun Zhang 0018 — Northwestern Polytechnical University, School of Astronautics, Shaanxi Aerospace Flight Vehicle Design Key Laboratory, Xi'an, China
- Kun Zhang 0019 — Southeast University, School of Economics and Management, Nanjing, China
- Kun Zhang 0020 — University of California San Diego, Department of Bioengineering, La Jolla, CA, USA
- Kun Zhang 0021 — Nanjing University of Science and Technology, School of Computer Science and Engineering, China
- Kun Zhang 0022 — Shenyang University of Technology, School of Materials Science and Engineering, China
- Kun Zhang 0023 — Shaanxi Provincial Tumor Hospital, Xi'an, China
- Kun Zhang 0024 — Chinese Academy of Sciences, Institute of Tibetan Plateau Research, Beijing, China (and 1 more)
- Kun Zhang 0025 — University of Science and Technology of China, CAS Key Laboratory of Wireless-Optical Communications, Hefei, China
- Kun Zhang 0026 — Shandong University of Science and Technology, College of Mechanical and Electronic Engineering, Qingdao, China (and 2 more)
- Kun Zhang 0027 — Huaqiao University, College of Tourism, Quanzhou, China
- Kun Zhang 0028 — University of Science and Technology of China, Department of Automation, Hefei, China
- Kun Zhang 0029 — Northwestern Polytechnical University, School of Electronics and Information, Xi'an, China
- Kun Zhang 0030 — Beihang University, Fert Beijing Research Institute, Beijing, China (and 2 more)
- Kun Zhang 0031 — Central China Normal University, National Engineering Laboratory for Educational Big Data and the National Engineering Research Center for E-Learning, Wuhan, China
- Kun Zhang 0032 — Luoyang Polytechnic, School of Automotive and Rail Transportation, Luoyang, China
- Kun Zhang 0033 — South China University of Technology, School of Electronics and Information Engineering, Guangzhou, China
- Kun Zhang 0034 — Xi'an Peihua University, School of Communication, Xi'an, China
- Kun Zhang 0035 — Nanjing University of Science and Technology, School of Computer Science and Engineering, Nanjing, China
- Kun Zhang 0036 — Renmin University of China, Institute of Statistics and Big Data, Beijing, China (and 1 more)
- Kun Zhang 0037 — Zhejiang Lab, Hangzhou, China
- Kun Zhang 0038 — Shandong University of Science and Technology, College of Intelligent Equipment, Tai'an, China
- Kun Zhang 0039 — Liaoning University, School of Mathematics, Shenyang, China
- Kun Zhang 0040 — University of Science and Technology of China, School of Information Science and Technology, Hefei, China (and 1 more)
- Kun Zhang 0041 — Chinese Academy of Sciences, Data Intelligence System Research Center, Institute of Computing Technology, China (and 1 more)
- Kun Zhang 0042 — Chinese Academy of Sciences, Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, HFIPS, Hefei, China (and 1 more)
- Kun Zhang 0043 — Google Inc., Google Health, Mountain View, CA, USA
- Kun Zhang 0044 — University of Electronic Science and Technology of China, School of Mechanical and Electrical Engineering, Chengdu, China
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2020 – today
- 2024
[j41]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): 573-584 (2024)- [j40]Weiwei Cai, Xuemiao Xu, Jiajia Xu, Huaidong Zhang, Haoxin Yang, Kun Zhang, Shengfeng He:
Hierarchical damage correlations for old photo restoration. Inf. Fusion 107: 102340 (2024) - [j39]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. J. Mach. Learn. Res. 25: 60:1-60:8 (2024) - [j38]Yuanyuan Wang, Wei Huang, Mingming Gong, Xi Geng, Tongliang Liu, Kun Zhang, Dacheng Tao:
Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations. J. Mach. Learn. Res. 25: 154:1-154:50 (2024) - [j37]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. J. Mach. Learn. Res. 25: 191:1-191:61 (2024) - [j36]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): 1932-1949 (2024) - [j35]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): 60:1-60:24 (2024) - [j34]Hanqi Yan, Lin Gui, Menghan Wang, Kun Zhang, Yulan He:
Explainable Recommender With Geometric Information Bottleneck. IEEE Trans. Knowl. Data Eng. 36(7): 3036-3046 (2024) - [j33]Weiwei Cai, Huaidong Zhang, Xuemiao Xu, Chenshu Xu, Kun Zhang, Shengfeng He:
Delving Into Important Samples of Semi-Supervised Old Photo Restoration: A New Dataset and Method. IEEE Trans. Multim. 26: 9866-9879 (2024) - [j32]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): 4899-4901 (2024) - [j31]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): 8854-8868 (2024) - [c170]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: 7278-7286 - [c169]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: 15193-15201 - [c168]Wei Chen, Zhiyi Huang, Ruichu Cai, Zhifeng Hao, Kun Zhang:
Identification of Causal Structure with Latent Variables Based on Higher Order Cumulants. AAAI 2024: 20353-20361 - [c167]Haoyue Dai, Ignavier Ng, Yujia Zheng, Zhengqing Gao, Kun Zhang:
Local Causal Discovery with Linear non-Gaussian Cyclic Models. AISTATS 2024: 154-162 - [c166]Ignavier Ng, Biwei Huang, Kun Zhang:
Structure Learning with Continuous Optimization: A Sober Look and Beyond. CLeaR 2024: 71-105 - [c165]Yuke Li, Lixiong Chen, Guangyi Chen, Ching-Yao Chan, Kun Zhang, Stefano Anzellotti, Donglai Wei:
Learning Socio-Temporal Graphs for Multi-Agent Trajectory Prediction. HCMA@MM 2024: 55-64 - [c164]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 - [c163]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 - [c162]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 - [c161]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 - [c160]Longkang Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang:
Federated Causal Discovery from Heterogeneous Data. ICLR 2024 - [c159]Xiu-Chuan Li, Kun Zhang, Tongliang Liu:
Causal Structure Recovery with Latent Variables under Milder Distributional and Graphical Assumptions. ICLR 2024 - [c158]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 - [c157]Zeyu Tang, Jialu Wang, Yang Liu, Peter Spirtes, Kun Zhang:
Procedural Fairness Through Decoupling Objectionable Data Generating Components. ICLR 2024 - [c156]Kun Zhang, Shaoan Xie, Ignavier Ng, Yujia Zheng:
Causal Representation Learning from Multiple Distributions: A General Setting. ICML 2024 - [c155]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. ICML 2024 - [c154]Shunxing Fan, Mingming Gong, Kun Zhang:
On the Recoverability of Causal Relations from Temporally Aggregated I.I.D. Data. ICML 2024 - [c153]Ignavier Ng, Xinshuai Dong, Haoyue Dai, Biwei Huang, Peter Spirtes, Kun Zhang:
Score-Based Causal Discovery of Latent Variable Causal Models. ICML 2024 - [c152]Wenjie Wang, Biwei Huang, Feng Liu, Xinge You, Tongliang Liu, Kun Zhang, Mingming Gong:
Optimal Kernel Choice for Score Function-based Causal Discovery. ICML 2024 - [c151]Tianjun Yao, Yongqiang Chen, Zhenhao Chen, Kai Hu, Zhiqiang Shen, Kun Zhang:
Empowering Graph Invariance Learning with Deep Spurious Infomax. ICML 2024 - [c150]Yujia Zheng, Zeyu Tang, Yiwen Qiu, Bernhard Schölkopf, Kun Zhang:
Detecting and Identifying Selection Structure in Sequential Data. ICML 2024 - [c149]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: 287-300 - [c148]Tianjun Yao, Jiaqi Sun, Defu Cao, Kun Zhang, Guangyi Chen:
MuGSI: Distilling GNNs with Multi-Granularity Structural Information for Graph Classification. WWW 2024: 709-720 - [i165]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 abs/2401.05414 (2024) - [i164]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 abs/2401.09716 (2024) - [i163]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 abs/2401.14535 (2024) - [i162]Yewen Fan, Nian Si, Xiangchen Song, Kun Zhang:
Calibration-then-Calculation: A Variance Reduced Metric Framework in Deep Click-Through Rate Prediction Models. CoRR abs/2401.16692 (2024) - [i161]Chenxi Liu, Yongqiang Chen, Tongliang Liu, Mingming Gong, James Cheng, Bo Han, Kun Zhang:
Discovery of the Hidden World with Large Language Models. CoRR abs/2402.03941 (2024) - [i160]Kun Zhang, Shaoan Xie, Ignavier Ng, Yujia Zheng:
Causal Representation Learning from Multiple Distributions: A General Setting. CoRR abs/2402.05052 (2024) - [i159]Yuhang Liu, Zhen Zhang, Dong Gong, Biwei Huang, Mingming Gong, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi:
Revealing Multimodal Contrastive Representation Learning through Latent Partial Causal Models. CoRR abs/2402.06223 (2024) - [i158]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 abs/2402.12563 (2024) - [i157]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 abs/2402.12767 (2024) - [i156]Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang:
Federated Causal Discovery from Heterogeneous Data. CoRR abs/2402.13241 (2024) - [i155]Hanqi Yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric P. Xing, Yulan He, Kun Zhang:
Counterfactual Generation with Identifiability Guarantees. CoRR abs/2402.15309 (2024) - [i154]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 abs/2403.01015 (2024) - [i153]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 abs/2403.08743 (2024) - [i152]Haoyue Dai, Ignavier Ng, Yujia Zheng, Zhengqing Gao, Kun Zhang:
Local Causal Discovery with Linear non-Gaussian Cyclic Models. CoRR abs/2403.14843 (2024) - [i151]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 abs/2403.15500 (2024) - [i150]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 abs/2403.15711 (2024) - [i149]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 abs/2404.13792 (2024) - [i148]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 abs/2405.15325 (2024) - [i147]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 abs/2405.16083 (2024) - [i146]Lingjing Kong, Guangyi Chen, Biwei Huang, Eric P. Xing, Yuejie Chi, Kun Zhang:
Learning Discrete Concepts in Latent Hierarchical Models. CoRR abs/2406.00519 (2024) - [i145]Shunxing Fan, Mingming Gong, Kun Zhang:
On the Recoverability of Causal Relations from Temporally Aggregated I.I.D. Data. CoRR abs/2406.02191 (2024) - [i144]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 abs/2406.06736 (2024) - [i143]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 abs/2406.07020 (2024) - [i142]Tianjun Yao, Jiaqi Sun, Defu Cao, Kun Zhang, Guangyi Chen:
MuGSI: Distilling GNNs with Multi-Granularity Structural Information for Graph Classification. CoRR abs/2406.19832 (2024) - [i141]Yujia Zheng, Zeyu Tang, Yiwen Qiu, Bernhard Schölkopf, Kun Zhang:
Detecting and Identifying Selection Structure in Sequential Data. CoRR abs/2407.00529 (2024) - [i140]Zhiqiang Xie, Yujia Zheng, Lizi Ottens, Kun Zhang, Christos Kozyrakis, Jonathan Mace:
Cloud Atlas: Efficient Fault Localization for Cloud Systems using Language Models and Causal Insight. CoRR abs/2407.08694 (2024) - [i139]Wenjie Wang, Biwei Huang, Feng Liu, Xinge You, Tongliang Liu, Kun Zhang, Mingming Gong:
Optimal Kernel Choice for Score Function-based Causal Discovery. CoRR abs/2407.10132 (2024) - [i138]Tianjun Yao, Yongqiang Chen, Zhenhao Chen, Kai Hu, Zhiqiang Shen, Kun Zhang:
Empowering Graph Invariance Learning with Deep Spurious Infomax. CoRR abs/2407.11083 (2024) - [i137]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 abs/2407.16975 (2024) - [i136]Yuqin Yang, Mohamed S. Nafea, Negar Kiyavash, Kun Zhang, AmirEmad Ghassami:
Causal Discovery in Linear Models with Unobserved Variables and Measurement Error. CoRR abs/2407.19426 (2024) - [i135]Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Xiangwei Chen, Zexu Sun, Fei Wu, Kun Zhang:
Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression. CoRR abs/2408.05428 (2024) - [i134]Boyang Sun, Ignavier Ng, Guangyi Chen, Yifan Shen, Qirong Ho, Kun Zhang:
Continual Learning of Nonlinear Independent Representations. CoRR abs/2408.05788 (2024) - [i133]Ce Chen, Shaoli Huang, Xuelin Chen, Guangyi Chen, Xiaoguang Han, Kun Zhang, Mingming Gong:
CT4D: Consistent Text-to-4D Generation with Animatable Meshes. CoRR abs/2408.08342 (2024) - [i132]Ignavier Ng, Yujia Zheng, Xinshuai Dong, Kun Zhang:
On the Identifiability of Sparse ICA without Assuming Non-Gaussianity. CoRR abs/2408.10353 (2024) - [i131]Xiangchen Song, Zijian Li, Guangyi Chen, Yujia Zheng, Yewen Fan, Xinshuai Dong, Kun Zhang:
Causal Temporal Representation Learning with Nonstationary Sparse Transition. CoRR abs/2409.03142 (2024) - [i130]Berker Demirel, Lingjing Kong, Kun Zhang, Theofanis Karaletsos, Celestine Mendler-Dünner, Francesco Locatello:
Adjusting Pretrained Backbones for Performativity. CoRR abs/2410.04499 (2024) - [i129]Yingyu Lin, Yuxing Huang, Wenqin Liu, Haoran Deng, Ignavier Ng, Kun Zhang, Mingming Gong, Yi-An Ma, Biwei Huang:
A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery. CoRR abs/2410.06407 (2024) - [i128]Anpeng Wu, Kun Kuang, Minqin Zhu, Yingrong Wang, Yujia Zheng, Kairong Han, Baohong Li, Guangyi Chen, Fei Wu, Kun Zhang:
Causality for Large Language Models. CoRR abs/2410.15319 (2024) - [i127]Yiwen Qiu, Yujia Zheng, Kun Zhang:
Identifying Selections for Unsupervised Subtask Discovery. CoRR abs/2410.21616 (2024) - [i126]Klea Ziu, Slavomír Hanzely, Loka Li, Kun Zhang, Martin Takác, Dmitry Kamzolov:
ψDAG: Projected Stochastic Approximation Iteration for DAG Structure Learning. CoRR abs/2410.23862 (2024) - 2023
- [j30]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): 299:1-299:37 (2023) - [j29]Feng Xie, Yan Zeng, Zhengming Chen, Yangbo He, Zhi Geng, Kun Zhang:
Causal discovery of 1-factor measurement models in linear latent variable models with arbitrary noise distributions. Neurocomputing 526: 48-61 (2023) - [j28]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: iv (2023) - [j27]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): 5458-5469 (2023) - [j26]Hao Zhang, Yewei Xia, Kun Zhang, Shuigeng Zhou, Jihong Guan:
Conditional Independence Test Based on Residual Similarity. ACM Trans. Knowl. Discov. Data 17(8): 117:1-117:18 (2023) - [j25]Yuewen Sun, Kun Zhang, Changyin Sun:
Model-Based Transfer Reinforcement Learning Based on Graphical Model Representations. IEEE Trans. Neural Networks Learn. Syst. 34(2): 1035-1048 (2023) - [c147]Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello:
Causal Discovery with Score Matching on Additive Models with Arbitrary Noise. CLeaR 2023: 726-751 - [c146]Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello:
Scalable Causal Discovery with Score Matching. CLeaR 2023: 752-771 - [c145]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: 7918-7928 - [c144]Shaoan Xie, Yanwu Xu, Mingming Gong, Kun Zhang:
Unpaired Image-to-Image Translation with Shortest Path Regularization. CVPR 2023: 10177-10187 - [c143]Guangyi Chen, Zhenhao Chen, Shunxing Fan, Kun Zhang:
Unsupervised Sampling Promoting for Stochastic Human Trajectory Prediction. CVPR 2023: 17874-17884 - [c142]Shaoan Xie, Zhifei Zhang, Zhe Lin, Tobias Hinz, Kun Zhang:
SmartBrush: Text and Shape Guided Object Inpainting with Diffusion Model. CVPR 2023: 22428-22437 - [c141]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: 13899-13909 - [c140]Guangyi Chen, Weiran Yao, Xiangchen Song, Xinyue Li, Yongming Rao, Kun Zhang:
PLOT: Prompt Learning with Optimal Transport for Vision-Language Models. ICLR 2023 - [c139]Yewen Fan, Nian Si, Kun Zhang:
Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems. ICLR 2023 - [c138]Junlong Li, Guangyi Chen, Yansong Tang, Jinan Bao, Kun Zhang, Jie Zhou, Jiwen Lu:
GAIN: On the Generalization of Instructional Action Understanding. ICLR 2023 - [c137]Zeyu Tang, Yatong Chen, Yang Liu, Kun Zhang:
Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors. ICLR 2023 - [c136]Xinyi Wang, Michael Saxon, Jiachen Li, Hongyang Zhang, Kun Zhang, William Yang Wang:
Causal Balancing for Domain Generalization. ICLR 2023 - [c135]Shaoan Xie, Lingjing Kong, Mingming Gong, Kun Zhang:
Multi-domain image generation and translation with identifiability guarantees. ICLR 2023 - [c134]Yujia Zheng, Ignavier Ng, Yewen Fan, Kun Zhang:
Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks. ICLR 2023 - [c133]Ruichu Cai, Zhiyi Huang, Wei Chen, Zhifeng Hao, Kun Zhang:
Causal Discovery with Latent Confounders Based on Higher-Order Cumulants. ICML 2023: 3380-3407 - [c132]Shiming Chen, Wenjin Hou, Ziming Hong, Xiaohan Ding, Yibing Song, Xinge You, Tongliang Liu, Kun Zhang:
Evolving Semantic Prototype Improves Generative Zero-Shot Learning. ICML 2023: 4611-4622 - [c131]Yatong Chen, Zeyu Tang, Kun Zhang, Yang Liu:
Model Transferability with Responsive Decision Subjects. ICML 2023: 4921-4952 - [c130]Yang Liu, Hao Cheng, Kun Zhang:
Identifiability of Label Noise Transition Matrix. ICML 2023: 21475-21496 - [c129]Jiaqi Sun, Lin Zhang, Guangyi Chen, Peng Xu, Kun Zhang, Yujiu Yang:
Feature Expansion for Graph Neural Networks. ICML 2023: 33156-33176 - [c128]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: 39660-39673 - [c127]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: 1-5 - [c126]Tianjun Yao, Yingxu Wang, Kun Zhang, Shangsong Liang:
Improving the Expressiveness of K-hop Message-Passing GNNs by Injecting Contextualized Substructure Information. KDD 2023: 3070-3081 - [c125]Zijian Li, Ruichu Cai, Guangyi Chen, Boyang Sun, Zhifeng Hao, Kun Zhang:
Subspace Identification for Multi-Source Domain Adaptation. NeurIPS 2023 - [c124]Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang:
Identification of Nonlinear Latent Hierarchical Models. NeurIPS 2023 - [c123]Yuren Liu, Biwei Huang, Zhengmao Zhu, Hong-Long Tian, Mingming Gong, Yang Yu, Kun Zhang:
Learning World Models with Identifiable Factorization. NeurIPS 2023 - [c122]Ignavier Ng, Yujia Zheng, Xinshuai Dong, Kun Zhang:
On the Identifiability of Sparse ICA without Assuming Non-Gaussianity. NeurIPS 2023 - [c121]Xiangchen Song, Weiran Yao, Yewen Fan, Xinshuai Dong, Guangyi Chen, Juan Carlos Niebles, Eric P. Xing, Kun Zhang:
Temporally Disentangled Representation Learning under Unknown Nonstationarity. NeurIPS 2023 - [c120]Hanqi Yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric P. Xing, Yulan He, Kun Zhang:
Counterfactual Generation with Identifiability Guarantees. NeurIPS 2023 - [c119]Yujia Zheng, Kun Zhang:
Generalizing Nonlinear ICA Beyond Structural Sparsity. NeurIPS 2023 - [i125]Zeyu Tang, Yatong Chen, Yang Liu, Kun Zhang:
Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors. CoRR abs/2301.08987<