| ML4S: Learning causal skeleton from vicinal graphs P Ma, R Ding, H Dai, Y Jiang, S Wang, S Han, D Zhang Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 11 | 2022 |
| ML4C: Seeing causality through latent vicinity H Dai, R Ding, Y Jiang, S Han, D Zhang SIAM International Conference on Data Mining (SDM 2023), 2021 | 8 | 2021 |
| Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models H Dai, P Spirtes, K Zhang Advances in Neural Information Processing Systems (NeurIPS 2022), 2022 | 7 | 2022 |
| What do CNN neurons learn: Visualization & Clustering H Dai arXiv preprint arXiv:2010.11725, 2020 | 1 | 2020 |
| 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 (AISTATS …, 2024 | | 2024 |
| Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View H Dai, I Ng, G Luo, P Stojanov, P Spirtes, K Zhang International Conference on Learning Representations (ICLR 2024), 2024 | | 2024 |
| On the Three Demons in Causality in Finance: Time Resolution, Nonstationarity, and Latent Factors X Dong, H Dai, Y Fan, S Jin, S Rajendran, K Zhang arXiv preprint arXiv:2401.05414, 2023 | | 2023 |
