Weilin Chen

According to our database, Weilin Chen authored at least 15 papers between 2021 and 2025.

Collaborative distances:

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

2025

Long-term causal effects estimation across domains: an invariant surrogate representation learning approach.

Jiabi Zheng, Weilin Chen, Zhiyong Lin, Aqing Yang, Zhifeng Hao

Int. J. Mach. Learn. Cybern., August, 2025

Horizontal and Vertical Federated Causal Structure Learning via Higher-order Cumulants.

Weilin Chen, Wanyang Gu, Linjun Peng, Ruichu Cai, Zhifeng Hao, Kun Zhang

CoRR, July, 2025

Long-term Causal Inference via Modeling Sequential Latent Confounding.

Weilin Chen, Ruichu Cai, Yuguang Yan, Zhifeng Hao, José Miguel Hernández-Lobato

CoRR, February, 2025

Nonparametric Heterogeneous Long-term Causal Effect Estimation via Data Combination.

Weilin Chen, Ruichu Cai, Junjie Wan, Zeqin Yang, José Miguel Hernández-Lobato

CoRR, February, 2025

On the Role of Entropy-Based Loss for Learning Causal Structure With Continuous Optimization.

Weilin Chen, Jie Qiao, Ruichu Cai, Zhifeng Hao

IEEE Trans. Neural Networks Learn. Syst., January, 2025

Learning Disentangled Representation for Multi-Modal Time-Series Sensing Signals.

Ruichu Cai, Zhifan Jiang, Kaitao Zheng, Zijian Li, Weilin Chen, Xuexin Chen, Yifan Shen, Guangyi Chen, Zhifeng Hao, Kun Zhang

Proceedings of the ACM on Web Conference 2025, 2025

Long-Term Individual Causal Effect Estimation via Identifiable Latent Representation Learning.

Ruichu Cai, Junjie Wan, Weilin Chen, Zeqin Yang, Zijian Li, Peng Zhen, Jiecheng Guo

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

2024

Long-term causal effects estimation via latent surrogates representation learning.

Ruichu Cai, Weilin Chen, Zeqin Yang, Shu Wan, Chen Zheng, Xiaoqing Yang, Jiecheng Guo

Neural Networks, 2024

Estimating Long-term Heterogeneous Dose-response Curve: Generalization Bound Leveraging Optimal Transport Weights.

Zeqin Yang, Weilin Chen, Ruichu Cai, Yuguang Yan, Zhifeng Hao, Zhipeng Yu, Zhichao Zou, Zhen Peng, Jiecheng Guo

CoRR, 2024

From Orthogonality to Dependency: Learning Disentangled Representation for Multi-Modal Time-Series Sensing Signals.

Ruichu Cai, Zhifang Jiang, Zijian Li, Weilin Chen, Xuexin Chen, Zhifeng Hao, Yifan Shen, Guangyi Chen, Kun Zhang

CoRR, 2024

Reducing Balancing Error for Causal Inference via Optimal Transport.

Yuguang Yan, Hao Zhou, Zeqin Yang, Weilin Chen, Ruichu Cai, Zhifeng Hao

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

Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning.

Weilin Chen, Ruichu Cai, Zeqin Yang, Jie Qiao, Yuguang Yan, Zijian Li, Zhifeng Hao

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

Exploiting Geometry for Treatment Effect Estimation via Optimal Transport.

Yuguang Yan, Zeqin Yang, Weilin Chen, Ruichu Cai, Zhifeng Hao, Michael Kwok-Po Ng

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Generalization Bound for Estimating Causal Effects from Observational Network Data.

Ruichu Cai, Zeqin Yang, Weilin Chen, Yuguang Yan, Zhifeng Hao

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2021

On the Role of Entropy-based Loss for Learning Causal Structures with Continuous Optimization.

Ruichu Cai, Weilin Chen, Jie Qiao, Zhifeng Hao

CoRR, 2021