| Causal discovery with reinforcement learning S Zhu, I Ng, Z Chen International Conference on Learning Representations, 2020 | 356 | 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 | 287 | 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 | 142 | 2022 |
| A Graph Autoencoder Approach to Causal Structure Learning I Ng, S Zhu, Z Chen, Z Fang arXiv preprint arXiv:1911.07420, 2019 | 131 | 2019 |
| On the Identifiability of Nonlinear ICA: Sparsity and Beyond Y Zheng, I Ng, K Zhang Advances in Neural Information Processing Systems 35, 2022 | 114 | 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 | 97 | 2021 |
| Towards federated Bayesian network structure learning with continuous optimization I Ng, K Zhang International Conference on Artificial Intelligence and Statistics, 8095-8111, 2022 | 57 | 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 | 57 | 2022 |
| Causal representation learning from multiple distributions: A general setting K Zhang, S Xie, I Ng, Y Zheng arXiv preprint arXiv:2402.05052, 2024 | 56 | 2024 |
| 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 | 46 | 2022 |
| Structure learning with continuous optimization: A sober look and beyond I Ng, B Huang, K Zhang Causal Learning and Reasoning, 71-105, 2024 | 42 | 2024 |
| 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 | 36 | 2021 |
| 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 | 35 | 2022 |
| 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 | 32 | 2022 |
| 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 | 29 | 2023 |
| 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 | 25 | 2018 |
| Federated causal discovery from heterogeneous data L Li, I Ng, G Luo, B Huang, G Chen, T Liu, B Gu, K Zhang arXiv preprint arXiv:2402.13241, 2024 | 21 | 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 | 14 | 2024 |
| Score-based causal discovery of latent variable causal models I Ng, X Dong, H Dai, B Huang, P Spirtes, K Zhang Forty-first International Conference on Machine Learning, 2024 | 11 | 2024 |
| On the identifiability of sparse ica without assuming non-gaussianity I Ng, Y Zheng, X Dong, K Zhang Advances in Neural Information Processing Systems 36, 47960-47990, 2023 | 8 | 2023 |
