Haoyue Dai

According to our database, Haoyue Dai authored at least 17 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Identification of Causal Direction under an Arbitrary Number of Latent Confounders.

Wei Chen, Linjun Peng, Zhiyi Huang, Haoyue Dai, Zhifeng Hao, Ruichu Cai, Kun Zhang

CoRR, October, 2025

Score-based Greedy Search for Structure Identification of Partially Observed Linear Causal Models.

Xinshuai Dong, Ignavier Ng, Haoyue Dai, Jiaqi Sun, Xiangchen Song, Peter Spirtes, Kun Zhang

CoRR, October, 2025

Characterization and Learning of Causal Graphs with Latent Confounders and Post-treatment Selection from Interventional Data.

Gongxu Luo, Loka Li, Guangyi Chen, Haoyue Dai, Kun Zhang

CoRR, September, 2025

Gene Regulatory Network Inference in the Presence of Selection Bias and Latent Confounders.

Gongxu Luo, Haoyue Dai, Boyang Sun, Loka Li, Biwei Huang, Petar Stojanov, Kun Zhang

CoRR, January, 2025

Permutation-based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data.

Xinshuai Dong, Ignavier Ng, Boyang Sun, Haoyue Dai, Guang-Yuan Hao, Shunxing Fan, Peter Spirtes, Yumou Qiu, Kun Zhang

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Latent Variable Causal Discovery under Selection Bias.

Haoyue Dai, Yiwen Qiu, Ignavier Ng, Xinshuai Dong, Peter Spirtes, Kun Zhang

Proceedings of the Forty-second International Conference on Machine Learning, 2025

When Selection Meets Intervention: Additional Complexities in Causal Discovery.

Haoyue Dai, Ignavier Ng, Jianle Sun, Zeyu Tang, Gongxu Luo, Xinshuai Dong, Peter Spirtes, Kun Zhang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Type Information-Assisted Self-Supervised Knowledge Graph Denoising.

Jiaqi Sun, Yujia Zheng, Xinshuai Dong, Haoyue Dai, Kun Zhang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

On the Three Demons in Causality in Finance: Time Resolution, Nonstationarity, and Latent Factors.

Xinshuai Dong, Haoyue Dai, Yewen Fan, Songyao Jin, Sathyamoorthy Rajendran, Kun Zhang

CoRR, 2024

On Causal Discovery in the Presence of Deterministic Relations.

Loka Li, Haoyue Dai, Hanin Al Ghothani, Biwei Huang, Jiji Zhang, Shahar Harel, Isaac Bentwich, Guangyi Chen, Kun Zhang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Score-Based Causal Discovery of Latent Variable Causal Models.

Ignavier Ng, Xinshuai Dong, Haoyue Dai, Biwei Huang, Peter Spirtes, Kun Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View.

Haoyue Dai, Ignavier Ng, Gongxu Luo, Peter Spirtes, Petar Stojanov, Kun Zhang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Local Causal Discovery with Linear non-Gaussian Cyclic Models.

Haoyue Dai, Ignavier Ng, Yujia Zheng, Zhengqing Gao, Kun Zhang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

ML4C: Seeing Causality Through Latent Vicinity.

Haoyue Dai, Rui Ding, Yuanyuan Jiang, Shi Han, Dongmei Zhang

Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

2022

Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models.

Haoyue Dai, Peter Spirtes, Kun Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

ML4S: Learning Causal Skeleton from Vicinal Graphs.

Pingchuan Ma, Rui Ding, Haoyue Dai, Yuanyuan Jiang, Shuai Wang, Shi Han, Dongmei Zhang

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2020

What do CNN neurons learn: Visualization & Clustering.

Haoyue Dai

CoRR, 2020