Shu Wan

According to our database, Shu Wan authored at least 12 papers between 2022 and 2026.

Collaborative distances:

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

2026

The Good, the Bad, and the Ugly of Markov Boundary for Tabular Prediction.

Shu Wan, Abhinav Gorantla, Huan Liu, K. Selçuk Candan

CoRR, May, 2026

DAGverse: Building Document-Grounded Semantic DAGs from Scientific Papers.

Shu Wan, Saketh Vishnubhatla, Iskander Kushbay, Tom Heffernan, Aaron Belikoff, Raha Moraffah, Huan Liu

CoRR, March, 2026

Proxy-Guided Measurement Calibration.

Saketh Vishnubhatla, Shu Wan, Andre Harrison, Adrienne Raglin, Huan Liu

CoRR, March, 2026

Causality Guided Representation Learning for Cross-Style Hate Speech Detection.

Chengshuai Zhao, Shu Wan, Paras Sheth, Karan Patwa, K. Selçuk Candan, Huan Liu

Proceedings of the ACM Web Conference 2026, 2026

CausalBench+: Causal-Informed Machine Learning Benchmarking.

Ahmet Kapkiç, Pratanu Mandal, Abhinav Gorantla, Shu Wan, Ertugrul Çoban, Huan Liu, K. Selcuk Candan

Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining, 2026

2025

CausalBench: Causal Learning Research Streamlined.

Ahmet Kapkiç, Pratanu Mandal, Abhinav Gorantla, Shu Wan, Ertugrul Çoban, Paras Sheth, Huan Liu, K. Selçuk Candan

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

CausalBench-ER: Causally-Informed Explanations and Recommendations for Reproducible Benchmarking.

Ahmet Kapkiç, Pratanu Mandal, Abhinav Gorantla, Shu Wan, Ertugrul Çoban, Paras Sheth, Huan Liu, K. Selçuk Candan

Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025

CauSTream: Causal Spatio-Temporal Representation Learning for Streamflow Forecasting.

Shu Wan, Reepal Shah, John Sabo, Huan Liu, K. Selçuk Candan

Proceedings of the IEEE International Conference on Big Data, 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

Introducing CausalBench: A Flexible Benchmark Framework for Causal Analysis and Machine Learning.

Ahmet Kapkiç, Pratanu Mandal, Shu Wan, Paras Sheth, Abhinav Gorantla, Yoonhyuk Choi, Huan Liu, K. Selçuk Candan

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Spatio-temporal Causal Learning for Streamflow Forecasting.

Shu Wan, Reepal Shah, Qi Deng, John Sabo, Huan Liu, K. Selçuk Candan

Proceedings of the IEEE International Conference on Big Data, 2024

2022

GCF: Generalized Causal Forest for Heterogeneous Treatment Effect Estimation in Online Marketplace.

Shu Wan, Chen Zheng, Zhonggen Sun, Mengfan Xu, Xiaoqing Yang, Hongtu Zhu, Jiecheng Guo

CoRR, 2022