More from the Same Authors

• 2022 : Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors »
  Zeyu Tang · Yatong Chen · Yang Liu · Kun Zhang
• 2022 : Scalable Causal Discovery with Score Matching »
  Francesco Montagna · Nicoletta Noceti · Lorenzo Rosasco · Kun Zhang · Francesco Locatello
• 2023 Poster: On the Identifiability of Sparse ICA without Assuming Non-Gaussianity »
  Ignavier Ng · Yujia Zheng · Xinshuai Dong · Kun Zhang
• 2023 Poster: Generalizing Nonlinear ICA Beyond Structural Sparsity »
  Yujia Zheng · Kun Zhang
• 2023 Poster: Counterfactual Generation with Identifiability Guarantee »
  hanqi yan · Lingjing Kong · Lin Gui · Yuejie Chi · Eric Xing · Yulan He · Kun Zhang
• 2023 Poster: Temporally Disentangled Representation Learning under Unknown Nonstationarity »
  Xiangchen Song · Weiran Yao · Yewen Fan · Xinshuai Dong · Guangyi Chen · Juan Carlos Niebles · Eric Xing · Kun Zhang
• 2023 Poster: Identification of Nonlinear Latent Hierarchical Models »
  Lingjing Kong · Biwei Huang · Feng Xie · Eric Xing · Yuejie Chi · Kun Zhang
• 2023 Poster: Subspace Identification for Multi-Source Domain Adaptation »
  Zijian Li · Ruichu Cai · Guangyi Chen · Boyang Sun · Zhifeng Hao · Kun Zhang
• 2023 Poster: Learning World Models with Identifiable Factorization »
  Yuren Liu · Biwei Huang · Zhengmao Zhu · Honglong Tian · Mingming Gong · Yang Yu · Kun Zhang
• 2023 Oral: Generalizing Nonlinear ICA Beyond Structural Sparsity »
  Yujia Zheng · Kun Zhang
• 2022 Spotlight: Latent Hierarchical Causal Structure Discovery with Rank Constraints »
  Biwei Huang · Charles Jia Han Low · Feng Xie · Clark Glymour · Kun Zhang
• 2022 : Kun Zhang: Causal Principles Meet Deep Learning: Successes and Challenges. »
  Kun Zhang
• 2022 : Kun Zhang: Causal Principles Meet Deep Learning: Successes and Challenges. »
  Kun Zhang
• 2022 Workshop: Causal Machine Learning for Real-World Impact »
  Nick Pawlowski · Jeroen Berrevoets · Caroline Uhler · Kun Zhang · Mihaela van der Schaar · Cheng Zhang
• 2022 Poster: On the Identifiability of Nonlinear ICA: Sparsity and Beyond »
  Yujia Zheng · Ignavier Ng · Kun Zhang
• 2022 Poster: Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models »
  Haoyue Dai · Peter Spirtes · Kun Zhang
• 2022 Poster: Latent Hierarchical Causal Structure Discovery with Rank Constraints »
  Biwei Huang · Charles Jia Han Low · Feng Xie · Clark Glymour · Kun Zhang
• 2022 Poster: MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models »
  Erdun Gao · Ignavier Ng · Mingming Gong · Li Shen · Wei Huang · Tongliang Liu · Kun Zhang · Howard Bondell
• 2022 Poster: Causal Discovery in Linear Latent Variable Models Subject to Measurement Error »
  Yuqin Yang · AmirEmad Ghassami · Mohamed Nafea · Negar Kiyavash · Kun Zhang · Ilya Shpitser
• 2022 Poster: Unsupervised Image-to-Image Translation with Density Changing Regularization »
  Shaoan Xie · Qirong Ho · Kun Zhang
• 2022 Poster: Factored Adaptation for Non-Stationary Reinforcement Learning »
  Fan Feng · Biwei Huang · Kun Zhang · Sara Magliacane
• 2022 Poster: Counterfactual Fairness with Partially Known Causal Graph »
  Aoqi Zuo · Susan Wei · Tongliang Liu · Bo Han · Kun Zhang · Mingming Gong
• 2022 Poster: Temporally Disentangled Representation Learning »
  Weiran Yao · Guangyi Chen · Kun Zhang
• 2022 Poster: Truncated Matrix Power Iteration for Differentiable DAG Learning »
  Zhen Zhang · Ignavier Ng · Dong Gong · Yuhang Liu · Ehsan Abbasnejad · Mingming Gong · Kun Zhang · Javen Qinfeng Shi
• 2021 Poster: Domain Adaptation with Invariant Representation Learning: What Transformations to Learn? »
  Petar Stojanov · Zijian Li · Mingming Gong · Ruichu Cai · Jaime Carbonell · Kun Zhang
• 2021 Poster: Identification of Partially Observed Linear Causal Models: Graphical Conditions for the Non-Gaussian and Heterogeneous Cases »
  Jeffrey Adams · Niels Hansen · Kun Zhang
• 2021 Poster: Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions »
  Ignavier Ng · Yujia Zheng · Jiji Zhang · Kun Zhang
• 2021 Poster: Instance-dependent Label-noise Learning under a Structural Causal Model »
  Yu Yao · Tongliang Liu · Mingming Gong · Bo Han · Gang Niu · Kun Zhang
• 2020 Workshop: Causal Discovery and Causality-Inspired Machine Learning »
  Biwei Huang · Sara Magliacane · Kun Zhang · Danielle Belgrave · Elias Bareinboim · Daniel Malinsky · Thomas Richardson · Christopher Meek · Peter Spirtes · Bernhard Schölkopf
• 2020 Poster: On the Role of Sparsity and DAG Constraints for Learning Linear DAGs »
  Ignavier Ng · AmirEmad Ghassami · Kun Zhang
• 2020 Poster: A Causal View on Robustness of Neural Networks »
  Cheng Zhang · Kun Zhang · Yingzhen Li
• 2020 Poster: How do fair decisions fare in long-term qualification? »
  Xueru Zhang · Ruibo Tu · Yang Liu · Mingyan Liu · Hedvig Kjellstrom · Kun Zhang · Cheng Zhang
• 2020 Poster: Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs »
  Feng Xie · Ruichu Cai · Biwei Huang · Clark Glymour · Zhifeng Hao · Kun Zhang
• 2020 Spotlight: Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs »
  Feng Xie · Ruichu Cai · Biwei Huang · Clark Glymour · Zhifeng Hao · Kun Zhang
• 2020 Poster: Domain Adaptation as a Problem of Inference on Graphical Models »
  Kun Zhang · Mingming Gong · Petar Stojanov · Biwei Huang · QINGSONG LIU · Clark Glymour
• 2019 Poster: Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation »
  Ruibo Tu · Kun Zhang · Bo Bertilson · Hedvig Kjellstrom · Cheng Zhang
• 2019 Poster: Triad Constraints for Learning Causal Structure of Latent Variables »
  Ruichu Cai · Feng Xie · Clark Glymour · Zhifeng Hao · Kun Zhang
• 2019 Poster: Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering »
  Biwei Huang · Kun Zhang · Pengtao Xie · Mingming Gong · Eric Xing · Clark Glymour
• 2019 Poster: Twin Auxilary Classifiers GAN »
  Mingming Gong · Yanwu Xu · Chunyuan Li · Kun Zhang · Kayhan Batmanghelich
• 2019 Spotlight: Twin Auxilary Classifiers GAN »
  Mingming Gong · Yanwu Xu · Chunyuan Li · Kun Zhang · Kayhan Batmanghelich
• 2019 Poster: Likelihood-Free Overcomplete ICA and Applications In Causal Discovery »
  Chenwei DING · Mingming Gong · Kun Zhang · Dacheng Tao
• 2019 Spotlight: Likelihood-Free Overcomplete ICA and Applications In Causal Discovery »
  Chenwei DING · Mingming Gong · Kun Zhang · Dacheng Tao
• 2018 : Invited Talk 1 »
  Marina Meila
• 2018 Poster: How to tell when a clustering is (approximately) correct using convex relaxations »
  Marina Meila
• 2018 Poster: Multi-domain Causal Structure Learning in Linear Systems »
  AmirEmad Ghassami · Negar Kiyavash · Biwei Huang · Kun Zhang
• 2018 Poster: Causal Discovery from Discrete Data using Hidden Compact Representation »
  Ruichu Cai · Jie Qiao · Kun Zhang · Zhenjie Zhang · Zhifeng Hao
• 2018 Poster: Modeling Dynamic Missingness of Implicit Feedback for Recommendation »
  Menghan Wang · Mingming Gong · Xiaolin Zheng · Kun Zhang
• 2017 : Topological Data Analisys with GUDHI and scalable manifold learning and clustering with megaman »
  Vincent Rouvreau · Marina Meila
• 2017 : Discussion: Geometric Data Analysis »
  Frederic Chazal · Marina Meila
• 2017 Workshop: Synergies in Geometric Data Analysis (TWO DAYS) »
  Marina Meila · Frederic Chazal · Yu-Chia Chen
• 2017 Poster: Learning Causal Structures Using Regression Invariance »
  AmirEmad Ghassami · Saber Salehkaleybar · Negar Kiyavash · Kun Zhang
• 2017 Poster: Improved Graph Laplacian via Geometric Self-Consistency »
  Dominique Perrault-Joncas · Marina Meila · James McQueen
• 2016 Poster: Nearly Isometric Embedding by Relaxation »
  James McQueen · Marina Meila · Dominique Perrault-Joncas
• 2016 Poster: Graph Clustering: Block-models and model free results »
  Yali Wan · Marina Meila
• 2015 Poster: A class of network models recoverable by spectral clustering »
  Yali Wan · Marina Meila
• 2014 Poster: Recursive Inversion Models for Permutations »
  Christopher Meek · Marina Meila
• 2011 Poster: Directed Graph Embedding: an Algorithm based on Continuous Limits of Laplacian-type Operators »
  Dominique C Perrault-Joncas · Marina Meila
• 2011 Spotlight: Directed Graph Embedding: an Algorithm based on Continuous Limits of Laplacian-type Operators »
  Dominique C Perrault-Joncas · Marina Meila
• 2009 Workshop: Learning with Orderings »
  Tiberio Caetano · Carlos Guestrin · Jonathan Huang · Risi Kondor · Guy Lebanon · Marina Meila