Causal discovery with reinforcement learning S Zhu, I Ng, Z Chen International Conference on Learning Representations, 2020 | 294 | 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 | 217 | 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 | 116 | 2022 |
A Graph Autoencoder Approach to Causal Structure Learning I Ng, S Zhu, Z Chen, Z Fang arXiv preprint arXiv:1911.07420, 2019 | 100 | 2019 |
On the Identifiability of Nonlinear ICA: Sparsity and Beyond Y Zheng, I Ng, K Zhang Advances in Neural Information Processing Systems 35, 2022 | 60 | 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 | 60 | 2021 |
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 | 43 | 2022 |
Towards federated bayesian network structure learning with continuous optimization I Ng, K Zhang International Conference on Artificial Intelligence and Statistics, 8095-8111, 2022 | 37 | 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 | 27 | 2022 |
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 | 26 | 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 | 26 | 2021 |
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 |
Structure learning with continuous optimization: A sober look and beyond I Ng, B Huang, K Zhang Causal Learning and Reasoning, 71-105, 2024 | 22 | 2024 |
Causal representation learning from multiple distributions: A general setting K Zhang, S Xie, I Ng, Y Zheng arXiv preprint arXiv:2402.05052, 2024 | 15 | 2024 |
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 | 15 | 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 | 13 | 2023 |
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 | 8 | 2022 |
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 | 5 | 2024 |
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 | 5 | 2024 |
Generalized precision matrix for scalable estimation of nonparametric markov networks Y Zheng, I Ng, Y Fan, K Zhang arXiv preprint arXiv:2305.11379, 2023 | 4 | 2023 |