| Causal discovery with reinforcement learning S Zhu, I Ng, Z Chen International Conference on Learning Representations, 2020 | 238 | 2020 |
| On the Role of Sparsity and DAG Constraints for Learning Linear DAGs I Ng, AE Ghassami, K Zhang Advances in Neural Information Processing Systems 33, 2020 | 150 | 2020 |
| Masked gradient-based causal structure learning I Ng*, S Zhu*, Z Fang*, H Li, Z Chen, J Wang Proceedings of the 2022 SIAM International Conference on Data Mining (SDM …, 2022 | 84 | 2022 |
| A Graph Autoencoder Approach to Causal Structure Learning I Ng, S Zhu, Z Chen, Z Fang arXiv preprint arXiv:1911.07420, 2019 | 77 | 2019 |
| On the Identifiability of Nonlinear ICA: Sparsity and Beyond Y Zheng, I Ng, K Zhang Advances in Neural Information Processing Systems 35, 2022 | 35 | 2022 |
| On the convergence of continuous constrained optimization for structure learning I Ng, S Lachapelle, NR Ke, S Lacoste-Julien, K Zhang International Conference on Artificial Intelligence and Statistics, 8176-8198, 2022 | 35 | 2022 |
| gcastle: A python toolbox for causal discovery K Zhang, S Zhu, M Kalander, I Ng, J Ye, Z Chen, L Pan arXiv preprint arXiv:2111.15155, 2021 | 34 | 2021 |
| Towards federated bayesian network structure learning with continuous optimization I Ng, K Zhang International Conference on Artificial Intelligence and Statistics, 8095-8111, 2022 | 24 | 2022 |
| Lipizzaner: a system that scales robust generative adversarial network training T Schmiedlechner, INZ Yong, A Al-Dujaili, E Hemberg, UM O'Reilly arXiv preprint arXiv:1811.12843, 2018 | 22 | 2018 |
| MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models E Gao*, I Ng*, M Gong, L Shen, W Huang, T Liu, K Zhang, H Bondell Advances in Neural Information Processing Systems 35, 2022 | 18 | 2022 |
| Truncated Matrix Power Iteration for Differentiable DAG Learning Z Zhang*, I Ng*, D Gong, Y Liu, EM Abbasnejad, M Gong, K Zhang, ... Advances in Neural Information Processing Systems 35, 2022 | 17 | 2022 |
| Reliable causal discovery with improved exact search and weaker assumptions I Ng, Y Zheng, J Zhang, K Zhang Advances in Neural Information Processing Systems 34, 20308-20320, 2021 | 17 | 2021 |
| STICC: a multivariate spatial clustering method for repeated geographic pattern discovery with consideration of spatial contiguity Y Kang, K Wu, S Gao, I Ng, J Rao, S Ye, F Zhang, T Fei International Journal of Geographical Information Science 36 (8), 1518-1549, 2022 | 9 | 2022 |
| On the identifiability of nonlinear ica with unconditional priors Y Zheng, I Ng, K Zhang ICLR2022 Workshop on the Elements of Reasoning: Objects, Structure and Causality, 2022 | 7 | 2022 |
| Structure learning with continuous optimization: A sober look and beyond I Ng, B Huang, K Zhang Causal Learning and Reasoning, 71-105, 2024 | 6 | 2024 |
| A versatile causal discovery framework to allow causally-related hidden variables X Dong, B Huang, I Ng, X Song, Y Zheng, S Jin, R Legaspi, P Spirtes, ... arXiv preprint arXiv:2312.11001, 2023 | 3 | 2023 |
| Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks Y Zheng, I Ng, Y Fan, K Zhang arXiv preprint arXiv:2305.11379, 2023 | 2 | 2023 |
| Causal Representation Learning from Multiple Distributions: A General Setting K Zhang, S Xie, I Ng, Y Zheng arXiv preprint arXiv:2402.05052, 2024 | 1 | 2024 |
| Local Causal Discovery with Linear non-Gaussian Cyclic Models H Dai, I Ng, Y Zheng, Z Gao, K Zhang International Conference on Artificial Intelligence and Statistics, 154-162, 2024 | | 2024 |
| Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View H Dai, I Ng, G Luo, P Spirtes, P Stojanov, K Zhang arXiv preprint arXiv:2403.15500, 2024 | | 2024 |
