Ignavier Ng - RankMe

63 papers A* 23A 5Journal 34Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Revisiting Differentiable Structure Learning: Inconsistency of L1 Penalty and Beyond. AAAI Kaifeng Jin, Ignavier Ng, Kun Zhang, Biwei Huang
2025	A*	`conf`	A General Representation-Based Approach to Multi-Source Domain Adaptation. ICML Ignavier Ng, Yan Li, Zijian Li, Yujia Zheng, Guangyi Chen, Kun Zhang
2025	A*	`conf`	A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery. ICLR Yingyu Lin, Yuxing Huang, Wenqin Liu, Haoran Deng, Ignavier Ng, Kun Zhang, Mingming Gong, Yian Ma, Biwei Huang
2025	A*	`conf`	Analytic DAG Constraints for Differentiable DAG Learning. ICLR Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Mingming Gong, Biwei Huang, Kun Zhang, Anton van den Hengel, Javen Qinfeng Shi
2025	J	`jnl`	Analytic DAG Constraints for Differentiable DAG Learning. CoRR Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Mingming Gong, Biwei Huang, Kun Zhang, Anton van den Hengel, Javen Qinfeng Shi
2025	A	`conf`	Causal Representation Learning from General Environments under Nonparametric Mixing. AISTATS Ignavier Ng, Shaoan Xie, Xinshuai Dong, Peter Spirtes, Kun Zhang
2025	J	`jnl`	Debiasing Reward Models by Representation Learning with Guarantees. CoRR Ignavier Ng, Patrick Blöbaum, Siddharth Bhandari, Kun Zhang, Shiva Prasad Kasiviswanathan
2025	A*	`conf`	Differentiable Causal Discovery for Latent Hierarchical Causal Models. ICLR Parjanya Prajakta Prashant, Ignavier Ng, Kun Zhang, Biwei Huang
2025	J	`jnl`	Higher-Order Causal Structure Learning with Additive Models. CoRR James Enouen, Yujia Zheng, Ignavier Ng, Yan Liu, Kun Zhang
2025	J	`jnl`	Identification of Nonparametric Dynamic Causal Structure and Latent Process in Climate System. CoRR Minghao Fu, Biwei Huang, Zijian Li, Yujia Zheng, Ignavier Ng, Yingyao Hu, Kun Zhang
2025	A*	`conf`	Latent Variable Causal Discovery under Selection Bias. ICML Haoyue Dai, Yiwen Qiu, Ignavier Ng, Xinshuai Dong, Peter Spirtes, Kun Zhang
2025	J	`jnl`	Latent Variable Causal Discovery under Selection Bias. CoRR Haoyue Dai, Yiwen Qiu, Ignavier Ng, Xinshuai Dong, Peter Spirtes, Kun Zhang
2025	J	`jnl`	Permutation-Based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data. CoRR Xinshuai Dong, Ignavier Ng, Boyang Sun, Haoyue Dai, Guang-Yuan Hao, Shunxing Fan, Peter Spirtes, Yumou Qiu, Kun Zhang
2025	A*	`conf`	Permutation-based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data. ICML Xinshuai Dong, Ignavier Ng, Boyang Sun, Haoyue Dai, Guang-Yuan Hao, Shunxing Fan, Peter Spirtes, Yumou Qiu, Kun Zhang
2025	J	`jnl`	Score-based Greedy Search for Structure Identification of Partially Observed Linear Causal Models. CoRR Xinshuai Dong, Ignavier Ng, Haoyue Dai, Jiaqi Sun, Xiangchen Song, Peter Spirtes, Kun Zhang
2025	A*	`conf`	Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning. ICLR Zijian Li, Shunxing Fan, Yujia Zheng, Ignavier Ng, Shaoan Xie, Guangyi Chen, Xinshuai Dong, Ruichu Cai, Kun Zhang
2025	J	`jnl`	Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning. CoRR Zijian Li, Shunxing Fan, Yujia Zheng, Ignavier Ng, Shaoan Xie, Guangyi Chen, Xinshuai Dong, Ruichu Cai, Kun Zhang
2025	A*	`conf`	When Selection Meets Intervention: Additional Complexities in Causal Discovery. ICLR Haoyue Dai, Ignavier Ng, Jianle Sun, Zeyu Tang, Gongxu Luo, Xinshuai Dong, Peter Spirtes, Kun Zhang
2025	J	`jnl`	When Selection Meets Intervention: Additional Complexities in Causal Discovery. CoRR Haoyue Dai, Ignavier Ng, Jianle Sun, Zeyu Tang, Gongxu Luo, Xinshuai Dong, Peter Spirtes, Kun Zhang
2024	J	`jnl`	A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery. CoRR Yingyu Lin, Yuxing Huang, Wenqin Liu, Haoran Deng, Ignavier Ng, Kun Zhang, Mingming Gong, Yi-An Ma, Biwei Huang
2024	A*	`conf`	A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables. ICLR Xinshuai Dong, Biwei Huang, Ignavier Ng, Xiangchen Song, Yujia Zheng, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
2024	A*	`conf`	Causal Representation Learning from Multiple Distributions: A General Setting. ICML Kun Zhang, Shaoan Xie, Ignavier Ng, Yujia Zheng
2024	J	`jnl`	Causal Representation Learning from Multiple Distributions: A General Setting. CoRR Kun Zhang, Shaoan Xie, Ignavier Ng, Yujia Zheng
2024	J	`jnl`	Continual Learning of Nonlinear Independent Representations. CoRR Boyang Sun, Ignavier Ng, Guangyi Chen, Yifan Shen, Qirong Ho, Kun Zhang
2024	J	`jnl`	Differentiable Causal Discovery For Latent Hierarchical Causal Models. CoRR Parjanya Prajakta Prashant, Ignavier Ng, Kun Zhang, Biwei Huang
2024	A*	`conf`	Federated Causal Discovery from Heterogeneous Data. ICLR Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang
2024	J	`jnl`	Federated Causal Discovery from Heterogeneous Data. CoRR Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang
2024	A*	`conf`	Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View. ICLR Haoyue Dai, Ignavier Ng, Gongxu Luo, Peter Spirtes, Petar Stojanov, Kun Zhang
2024	J	`jnl`	Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View. CoRR Haoyue Dai, Ignavier Ng, Gongxu Luo, Peter Spirtes, Petar Stojanov, Kun Zhang
2024	A	`conf`	Local Causal Discovery with Linear non-Gaussian Cyclic Models. AISTATS Haoyue Dai, Ignavier Ng, Yujia Zheng, Zhengqing Gao, Kun Zhang
2024	J	`jnl`	Local Causal Discovery with Linear non-Gaussian Cyclic Models. CoRR Haoyue Dai, Ignavier Ng, Yujia Zheng, Zhengqing Gao, Kun Zhang
2024	J	`jnl`	On the Identifiability of Sparse ICA without Assuming Non-Gaussianity. CoRR Ignavier Ng, Yujia Zheng, Xinshuai Dong, Kun Zhang
2024	A*	`conf`	On the Parameter Identifiability of Partially Observed Linear Causal Models. NeurIPS Xinshuai Dong, Ignavier Ng, Biwei Huang, Yuewen Sun, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
2024	J	`jnl`	On the Parameter Identifiability of Partially Observed Linear Causal Models. CoRR Xinshuai Dong, Ignavier Ng, Biwei Huang, Yuewen Sun, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
2024	J	`jnl`	Revisiting Differentiable Structure Learning: Inconsistency of ℓ CoRR Kaifeng Jin, Ignavier Ng, Kun Zhang, Biwei Huang
2024	A*	`conf`	Score-Based Causal Discovery of Latent Variable Causal Models. ICML Ignavier Ng, Xinshuai Dong, Haoyue Dai, Biwei Huang, Peter Spirtes, Kun Zhang
2024	—	`conf`	Structure Learning with Continuous Optimization: A Sober Look and Beyond. CLeaR Ignavier Ng, Biwei Huang, Kun Zhang
2023	J	`jnl`	A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables. CoRR Xinshuai Dong, Biwei Huang, Ignavier Ng, Xiangchen Song, Yujia Zheng, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
2023	A*	`conf`	Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks. ICLR Yujia Zheng, Ignavier Ng, Yewen Fan, Kun Zhang
2023	J	`jnl`	Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks. CoRR Yujia Zheng, Ignavier Ng, Yewen Fan, Kun Zhang
2023	A*	`conf`	On the Identifiability of Sparse ICA without Assuming Non-Gaussianity. NeurIPS Ignavier Ng, Yujia Zheng, Xinshuai Dong, Kun Zhang
2023	J	`jnl`	Structure Learning with Continuous Optimization: A Sober Look and Beyond. CoRR Ignavier Ng, Biwei Huang, Kun Zhang
2022	A	`conf`	Masked Gradient-Based Causal Structure Learning. SDM Ignavier Ng, Shengyu Zhu, Zhuangyan Fang, Haoyang Li, Zhitang Chen, Jun Wang
2022	A*	`conf`	MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models. NeurIPS Erdun Gao, Ignavier Ng, Mingming Gong, Li Shen, Wei Huang, Tongliang Liu, Kun Zhang, Howard D. Bondell
2022	J	`jnl`	MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models. CoRR Erdun Gao, Ignavier Ng, Mingming Gong, Li Shen, Wei Huang, Tongliang Liu, Kun Zhang, Howard D. Bondell
2022	A	`conf`	On the Convergence of Continuous Constrained Optimization for Structure Learning. AISTATS Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien, Kun Zhang
2022	A*	`conf`	On the Identifiability of Nonlinear ICA: Sparsity and Beyond. NeurIPS Yujia Zheng, Ignavier Ng, Kun Zhang
2022	J	`jnl`	On the Identifiability of Nonlinear ICA: Sparsity and Beyond. CoRR Yujia Zheng, Ignavier Ng, Kun Zhang
2022	J	`jnl`	Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions. CoRR Ignavier Ng, Yujia Zheng, Jiji Zhang, Kun Zhang
2022	J	`jnl`	STICC: A multivariate spatial clustering method for repeated geographic pattern discovery with consideration of spatial contiguity. CoRR Yuhao Kang, Kunlin Wu, Song Gao, Ignavier Ng, Jinmeng Rao, Shan Ye, Fan Zhang, Teng Fei
2022	J	`jnl`	STICC: a multivariate spatial clustering method for repeated geographic pattern discovery with consideration of spatial contiguity. Int. J. Geogr. Inf. Sci. Yuhao Kang, Kunlin Wu, Song Gao, Ignavier Ng, Jinmeng Rao, Shan Ye, Fan Zhang, Teng Fei
2022	A	`conf`	Towards Federated Bayesian Network Structure Learning with Continuous Optimization. AISTATS Ignavier Ng, Kun Zhang
2022	A*	`conf`	Truncated Matrix Power Iteration for Differentiable DAG Learning. NeurIPS Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Ehsan Abbasnejad, Mingming Gong, Kun Zhang, Javen Qinfeng Shi
2022	J	`jnl`	Truncated Matrix Power Iteration for Differentiable DAG Learning. CoRR Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, M. Ehsan Abbasnejad, Mingming Gong, Kun Zhang, Javen Qinfeng Shi
2021	A*	`conf`	Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions. NeurIPS Ignavier Ng, Yujia Zheng, Jiji Zhang, Kun Zhang
2021	J	`jnl`	Towards Federated Bayesian Network Structure Learning with Continuous Optimization. CoRR Ignavier Ng, Kun Zhang
2021	J	`jnl`	gCastle: A Python Toolbox for Causal Discovery. CoRR Keli Zhang, Shengyu Zhu, Marcus Kalander, Ignavier Ng, Junjian Ye, Zhitang Chen, Lujia Pan
2020	A*	`conf`	Causal Discovery with Reinforcement Learning. ICLR Shengyu Zhu, Ignavier Ng, Zhitang Chen
2020	J	`jnl`	On the Convergence of Continuous Constrained Optimization for Structure Learning. CoRR Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien
2020	A*	`conf`	On the Role of Sparsity and DAG Constraints for Learning Linear DAGs. NeurIPS Ignavier Ng, AmirEmad Ghassami, Kun Zhang
2020	J	`jnl`	On the Role of Sparsity and DAG Constraints for Learning Linear DAGs. CoRR Ignavier Ng, AmirEmad Ghassami, Kun Zhang
2019	J	`jnl`	A Graph Autoencoder Approach to Causal Structure Learning. CoRR Ignavier Ng, Shengyu Zhu, Zhitang Chen, Zhuangyan Fang
2019	J	`jnl`	Masked Gradient-Based Causal Structure Learning. CoRR Ignavier Ng, Zhuangyan Fang, Shengyu Zhu, Zhitang Chen