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2020 – today
- 2024
[c6]Haoyue Dai, Ignavier Ng, Yujia Zheng, Zhengqing Gao, Kun Zhang:
Local Causal Discovery with Linear non-Gaussian Cyclic Models. AISTATS 2024: 154-162- [c5]Haoyue Dai, Ignavier Ng, Gongxu Luo, Peter Spirtes, Petar Stojanov, Kun Zhang:
Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View. ICLR 2024 - [c4]Ignavier Ng, Xinshuai Dong, Haoyue Dai, Biwei Huang, Peter Spirtes, Kun Zhang:
Score-Based Causal Discovery of Latent Variable Causal Models. ICML 2024 - [i6]Xinshuai Dong, Haoyue Dai, Yewen Fan, Songyao Jin, Sathyamoorthy Rajendran
, Kun Zhang:
On the Three Demons in Causality in Finance: Time Resolution, Nonstationarity, and Latent Factors. CoRR abs/2401.05414 (2024) - [i5]Haoyue Dai, Ignavier Ng, Yujia Zheng, Zhengqing Gao, Kun Zhang:
Local Causal Discovery with Linear non-Gaussian Cyclic Models. CoRR abs/2403.14843 (2024) - [i4]Haoyue Dai, Ignavier Ng, Gongxu Luo, Peter Spirtes, Petar Stojanov, Kun Zhang:
Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View. CoRR abs/2403.15500 (2024) - 2023
- [c3]Haoyue Dai, Rui Ding, Yuanyuan Jiang, Shi Han, Dongmei Zhang:
ML4C: Seeing Causality Through Latent Vicinity. SDM 2023: 226-234 - 2022
- [c2]Pingchuan Ma, Rui Ding, Haoyue Dai, Yuanyuan Jiang, Shuai Wang, Shi Han, Dongmei Zhang:
ML4S: Learning Causal Skeleton from Vicinal Graphs. KDD 2022: 1213-1223 - [c1]Haoyue Dai, Peter Spirtes, Kun Zhang:
Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models. NeurIPS 2022 - [i3]Haoyue Dai, Peter Spirtes, Kun Zhang:
Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models. CoRR abs/2210.11021 (2022) - 2021
- [i2]Haoyue Dai, Rui Ding, Yuanyuan Jiang, Shi Han, Dongmei Zhang:
ML4C: Seeing Causality Through Latent Vicinity. CoRR abs/2110.00637 (2021) - 2020
- [i1]Haoyue Dai:
What do CNN neurons learn: Visualization & Clustering. CoRR abs/2010.11725 (2020)
Coauthor Index
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