Ng, Ignavier

29 publications

ICML 2025 A General Representation-Based Approach to Multi-Source Domain Adaptation Ignavier Ng, Yan Li, Zijian Li, Yujia Zheng, Guangyi Chen, Kun Zhang

ICLR 2025 A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery Yingyu Lin, Yuxing Huang, Wenqin Liu, Haoran Deng, Ignavier Ng, Kun Zhang, Mingming Gong, Yian Ma, Biwei Huang

ICLR 2025 Analytic DAG Constraints for Differentiable DAG Learning Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Mingming Gong, Biwei Huang, Kun Zhang, Anton van den Hengel, Javen Qinfeng Shi

AISTATS 2025 Causal Representation Learning from General Environments Under Nonparametric Mixing Ignavier Ng, Shaoan Xie, Xinshuai Dong, Peter Spirtes, Kun Zhang

ICLR 2025 Differentiable Causal Discovery for Latent Hierarchical Causal Models Parjanya Prajakta Prashant, Ignavier Ng, Kun Zhang, Biwei Huang

ICML 2025 Latent Variable Causal Discovery Under Selection Bias Haoyue Dai, Yiwen Qiu, Ignavier Ng, Xinshuai Dong, Peter Spirtes, Kun Zhang

ICML 2025 Permutation-Based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data Xinshuai Dong, Ignavier Ng, Boyang Sun, Haoyue Dai, Guang-Yuan Hao, Shunxing Fan, Peter Spirtes, Yumou Qiu, Kun Zhang

ICLR 2025 Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning Zijian Li, Shunxing Fan, Yujia Zheng, Ignavier Ng, Shaoan Xie, Guangyi Chen, Xinshuai Dong, Ruichu Cai, Kun Zhang

ICLR 2025 When Selection Meets Intervention: Additional Complexities in Causal Discovery Haoyue Dai, Ignavier Ng, Jianle Sun, Zeyu Tang, Gongxu Luo, Xinshuai Dong, Peter Spirtes, Kun Zhang

ICLR 2024 A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables Xinshuai Dong, Biwei Huang, Ignavier Ng, Xiangchen Song, Yujia Zheng, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang

ICML 2024 Causal Representation Learning from Multiple Distributions: A General Setting Kun Zhang, Shaoan Xie, Ignavier Ng, Yujia Zheng

NeurIPSW 2024 Differentiable Causal Discovery for Latent Hierarchical Causal Models Parjanya Prajakta Prashant, Ignavier Ng, Kun Zhang, Biwei Huang

ICLR 2024 Federated Causal Discovery from Heterogeneous Data Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang

ICLR 2024 Gene Regulatory Network Inference in the Presence of Dropouts: A Causal View Haoyue Dai, Ignavier Ng, Gongxu Luo, Peter Spirtes, Petar Stojanov, Kun Zhang

AISTATS 2024 Local Causal Discovery with Linear Non-Gaussian Cyclic Models Haoyue Dai, Ignavier Ng, Yujia Zheng, Zhengqing Gao, Kun Zhang

NeurIPS 2024 On the Parameter Identifiability of Partially Observed Linear Causal Models Xinshuai Dong, Ignavier Ng, Biwei Huang, Yuewen Sun, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang

ICML 2024 Score-Based Causal Discovery of Latent Variable Causal Models Ignavier Ng, Xinshuai Dong, Haoyue Dai, Biwei Huang, Peter Spirtes, Kun Zhang

CLeaR 2024 Structure Learning with Continuous Optimization: A Sober Look and Beyond Ignavier Ng, Biwei Huang, Kun Zhang

ICLR 2023 Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks Yujia Zheng, Ignavier Ng, Yewen Fan, Kun Zhang

NeurIPS 2023 On the Identifiability of Sparse ICA Without Assuming Non-Gaussianity Ignavier Ng, Yujia Zheng, Xinshuai Dong, Kun Zhang

AISTATS 2022 On the Convergence of Continuous Constrained Optimization for Structure Learning Ignavier Ng, Sebastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien, Kun Zhang

AISTATS 2022 Towards Federated Bayesian Network Structure Learning with Continuous Optimization Ignavier Ng, Kun Zhang

NeurIPS 2022 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

ICLRW 2022 On the Identifiability of Nonlinear ICA with Unconditional Priors Yujia Zheng, Ignavier Ng, Kun Zhang

NeurIPS 2022 On the Identifiability of Nonlinear ICA: Sparsity and Beyond Yujia Zheng, Ignavier Ng, Kun Zhang

NeurIPS 2022 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

NeurIPS 2021 Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions Ignavier Ng, Yujia Zheng, Jiji Zhang, Kun Zhang

ICLR 2020 Causal Discovery with Reinforcement Learning Shengyu Zhu, Ignavier Ng, Zhitang Chen

NeurIPS 2020 On the Role of Sparsity and DAG Constraints for Learning Linear DAGs Ignavier Ng, AmirEmad Ghassami, Kun Zhang