Ignavier Ng

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 36

Top Topics

Conditional Independence

Causal Discovery

Continuous Optimization

Heterogeneous Data

Top Venues

Publications

Ignavier Ng, Biwei Huang, Kun Zhang
Structure Learning with Continuous Optimization: A Sober Look and Beyond. CLeaR (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)
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)
Longkang Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang
Federated Causal Discovery from Heterogeneous Data. ICLR (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)
Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang
Federated Causal Discovery from Heterogeneous Data. CoRR (2024)
Haoyue Dai, Ignavier Ng, Yujia Zheng, Zhengqing Gao, Kun Zhang
Local Causal Discovery with Linear non-Gaussian Cyclic Models. CoRR (2024)
Haoyue Dai, Ignavier Ng, Yujia Zheng, Zhengqing Gao, Kun Zhang
Local Causal Discovery with Linear non-Gaussian Cyclic Models. AISTATS (2024)
Kun Zhang, Shaoan Xie, Ignavier Ng, Yujia Zheng
Causal Representation Learning from Multiple Distributions: A General Setting. CoRR (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)
Ignavier Ng, Biwei Huang, Kun Zhang
Structure Learning with Continuous Optimization: A Sober Look and Beyond. CoRR (2023)
Yujia Zheng, Ignavier Ng, Yewen Fan, Kun Zhang
Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks. CoRR (2023)
Ignavier Ng, Yujia Zheng, Xinshuai Dong, Kun Zhang
On the Identifiability of Sparse ICA without Assuming Non-Gaussianity. NeurIPS (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)
Yujia Zheng, Ignavier Ng, Yewen Fan, Kun Zhang
Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks. ICLR (2023)
Yujia Zheng, Ignavier Ng, Kun Zhang
On the Identifiability of Nonlinear ICA: Sparsity and Beyond. CoRR (2022)
Yuhao Kang, Kunlin Wu, Song Gao, Ignavier Ng, Jinmeng Rao, Shan Ye, Fan Zhang, Teng Fei
STICC: A multivariate spatial clustering method for repeated geographic pattern discovery with consideration of spatial contiguity. CoRR (2022)
Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Ehsan Abbasnejad, Mingming Gong, Kun Zhang, Javen Qinfeng Shi
Truncated Matrix Power Iteration for Differentiable DAG Learning. NeurIPS (2022)
Yujia Zheng, Ignavier Ng, Kun Zhang
On the Identifiability of Nonlinear ICA: Sparsity and Beyond. NeurIPS (2022)
Erdun Gao, Ignavier Ng, Mingming Gong, Li Shen, Wei Huang, Tongliang Liu, Kun Zhang, Howard D. Bondell
MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models. NeurIPS (2022)
Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, M. Ehsan Abbasnejad, Mingming Gong, Kun Zhang, Javen Qinfeng Shi
Truncated Matrix Power Iteration for Differentiable DAG Learning. CoRR (2022)
Ignavier Ng, Shengyu Zhu, Zhuangyan Fang, Haoyang Li, Zhitang Chen, Jun Wang
Masked Gradient-Based Causal Structure Learning. SDM (2022)
Yuhao Kang, Kunlin Wu, Song Gao, Ignavier Ng, Jinmeng Rao, Shan Ye, Fan Zhang, Teng Fei
STICC: a multivariate spatial clustering method for repeated geographic pattern discovery with consideration of spatial contiguity. Int. J. Geogr. Inf. Sci. 36 (8) (2022)
Ignavier Ng, Yujia Zheng, Jiji Zhang, Kun Zhang
Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions. CoRR (2022)
Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien, Kun Zhang
On the Convergence of Continuous Constrained Optimization for Structure Learning. AISTATS (2022)
Erdun Gao, Ignavier Ng, Mingming Gong, Li Shen, Wei Huang, Tongliang Liu, Kun Zhang, Howard Bondell
MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models. CoRR (2022)
Ignavier Ng, Kun Zhang
Towards Federated Bayesian Network Structure Learning with Continuous Optimization. AISTATS (2022)
Ignavier Ng, Kun Zhang
Towards Federated Bayesian Network Structure Learning with Continuous Optimization. CoRR (2021)
Keli Zhang, Shengyu Zhu, Marcus Kalander, Ignavier Ng, Junjian Ye, Zhitang Chen, Lujia Pan
gCastle: A Python Toolbox for Causal Discovery. CoRR (2021)
Ignavier Ng, Yujia Zheng, Jiji Zhang, Kun Zhang
Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions. NeurIPS (2021)
Ignavier Ng, AmirEmad Ghassami, Kun Zhang
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs. NeurIPS (2020)
Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien
On the Convergence of Continuous Constrained Optimization for Structure Learning. CoRR (2020)
Ignavier Ng, AmirEmad Ghassami, Kun Zhang
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs. CoRR (2020)
Shengyu Zhu, Ignavier Ng, Zhitang Chen
Causal Discovery with Reinforcement Learning. ICLR (2020)
Ignavier Ng, Zhuangyan Fang, Shengyu Zhu, Zhitang Chen
Masked Gradient-Based Causal Structure Learning. CoRR (2019)
Ignavier Ng, Shengyu Zhu, Zhitang Chen, Zhuangyan Fang
A Graph Autoencoder Approach to Causal Structure Learning. CoRR (2019)