Publications & Preprints

* denotes equal contribution

2024

  1. CLeaR
    Structure Learning with Continuous Optimization: A Sober Look and Beyond
    Ignavier Ng, Biwei Huang, and Kun Zhang
    Conference on Causal Learning and Reasoning, 2024 (Best Paper Award)
    PDF
  2. AISTATS
    Local Causal Discovery with Linear non-Gaussian Cyclic Models
    Haoyue Dai*, Ignavier Ng*, Yujia Zheng, Zhengqing Gao, and Kun Zhang
    International Conference on Artificial Intelligence and Statistics, 2024
    PDF
  3. ICLR
    Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View
    Haoyue Dai, Ignavier Ng, Gongxu Luo, Petar Stojanov, Peter Spirtes, and Kun Zhang
    International Conference on Learning Representations, 2024 (Oral)
    PDF
  4. ICLR
    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, and Kun Zhang
    International Conference on Learning Representations, 2024
    PDF
  5. ICLR
    Federated Causal Discovery from Heterogeneous Data
    Longkang Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, and Kun Zhang
    International Conference on Learning Representations, 2024
    PDF

2023

  1. NeurIPS
    On the Identifiability of Sparse ICA without Assuming Non-Gaussianity
    Ignavier Ng*, Yujia Zheng*, Xinshuai Dong, and Kun Zhang
    Advances in Neural Information Processing Systems, 2023
    PDF
  2. ICLR
    Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks
    Yujia Zheng, Ignavier Ng, Yewen Fan, and Kun Zhang
    International Conference on Learning Representations, 2023
    PDF

2022

  1. NeurIPS
    Truncated Matrix Power Iteration for Differentiable DAG Learning
    Zhen Zhang*, Ignavier Ng*, Dong Gong, Yuhang Liu, Ehsan M Abbasnejad, Mingming Gong, Kun Zhang, and Javen Qinfeng Shi
    Advances in Neural Information Processing Systems, 2022
    PDF Code
  2. NeurIPS
    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, and Howard Bondell
    Advances in Neural Information Processing Systems, 2022
    PDF Code
  3. NeurIPS
    On the Identifiability of Nonlinear ICA: Sparsity and Beyond
    Yujia Zheng, Ignavier Ng, and Kun Zhang
    Advances in Neural Information Processing Systems, 2022
    ICLR Workshop on Objects, Structure, and Causality,     2022 (Oral)
    PDF
  4. AISTATS
    On the Convergence of Continuous Constrained Optimization for Structure Learning
    Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien, and Kun Zhang
    International Conference on Artificial Intelligence and Statistics, 2022
    NeurIPS Workshop on Causal Discovery and Causality-Inspired Machine Learning,     2020 (Oral)
    PDF Code
  5. AISTATS
    Towards Federated Bayesian Network Structure Learning with Continuous Optimization
    Ignavier Ng and Kun Zhang
    International Conference on Artificial Intelligence and Statistics, 2022
    PDF Code
  6. SDM
    Masked Gradient-Based Causal Structure Learning
    Ignavier Ng*, Shengyu Zhu*, Zhuangyan Fang*, Haoyang Li, Zhitang Chen, and Jun Wang
    SIAM International Conference on Data Mining, 2022
    PDF Code
  7. IJGIS
    STICC: a multivariate spatial clustering method for repeated geographic pattern discovery with consideration of spatial contiguity
    Yuhao Kang, Kunlin Wu, Song Gao, Ignavier Ng, Jinmeng Rao, Shan Ye, Fan Zhang, and Teng Fei
    International Journal of Geographical Information Science, 2022
    PDF Code

2021

  1. NeurIPS
    Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions
    Ignavier Ng, Yujia Zheng, Jiji Zhang, and Kun Zhang
    Advances in Neural Information Processing Systems, 2021
    PDF Code
  2. arXiv
    gCastle: A Python Toolbox for Causal Discovery
    Keli Zhang*, Shengyu Zhu*, Marcus Kalander, Ignavier Ng, Junjian Ye, Zhitang Chen, and Lujia Pan
    arXiv preprint arXiv:2111.15155, 2021
    PDF Code

2020

  1. NeurIPS
    On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
    Ignavier Ng, AmirEmad Ghassami, and Kun Zhang
    Advances in Neural Information Processing Systems, 2020
    PDF Code
  2. ICLR
    Causal Discovery with Reinforcement Learning
    Shengyu Zhu, Ignavier Ng, and Zhitang Chen
    International Conference on Learning Representations, 2020 (Oral)
    PDF Code