Erhu He

According to our database, Erhu He authored at least 14 papers between 2021 and 2024.

Collaborative distances:

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

2024

Learning With Location-Based Fairness: A Statistically-Robust Framework and Acceleration.

Erhu He, Yiqun Xie, Weiye Chen, Sergii Skakun, Han Bao, Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia

IEEE Trans. Knowl. Data Eng., September, 2024

Physics-Guided Fair Graph Sampling for Water Temperature Prediction in River Networks.

Erhu He, Declan Kutscher, Yiqun Xie, Jacob Zwart, Zhe Jiang, Huaxiu Yao, Xiaowei Jia

CoRR, 2024

Knowledge Guided Machine Learning for Extracting, Preserving, and Adapting Physics-aware Features.

Erhu He, Yiqun Xie, Licheng Liu, Zhenong Jin, Dajun Zhang, Xiaowei Jia

Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

PAIL: Performance based Adversarial Imitation Learning Engine for Carbon Neutral Optimization.

Yuyang Ye, Lu-An Tang, Haoyu Wang, Runlong Yu, Wenchao Yu, Erhu He, Haifeng Chen, Hui Xiong

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Fair Graph Learning Using Constraint-Aware Priority Adjustment and Graph Masking in River Networks.

Erhu He, Yiqun Xie, Alexander Sun, Jacob Zwart, Jie Yang, Zhenong Jin, Yang Wang, Hassan A. Karimi, Xiaowei Jia

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

Referee-Meta-Learning for Fast Adaptation of Locational Fairness.

Weiye Chen, Yiqun Xie, Xiaowei Jia, Erhu He, Han Bao, Bang An, Xun Zhou

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

2023

Harnessing heterogeneity in space with statistically guided meta-learning.

Yiqun Xie, Weiye Chen, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh, Praveen Ravirathinam

Knowl. Inf. Syst., June, 2023

Entity Aware Modelling: A Survey.

Rahul Ghosh, Haoyu Yang, Ankush Khandelwal, Erhu He, Arvind Renganathan, Somya Sharma, Xiaowei Jia, Vipin Kumar

CoRR, 2023

CGS: Coupled Growth and Survival Model with Cohort Fairness.

Erhu He, Yue Wan, Benjamin H. Letcher, Jennifer H. Fair, Yiqun Xie, Xiaowei Jia

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Physics Guided Neural Networks for Time-Aware Fairness: An Application in Crop Yield Prediction.

Erhu He, Yiqun Xie, Licheng Liu, Weiye Chen, Zhenong Jin, Xiaowei Jia

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Statistically-Guided Deep Network Transformation to Harness Heterogeneity in Space (Extended Abstract).

Yiqun Xie, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh, Praveen Ravirathinam

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Sailing in the location-based fairness-bias sphere.

Erhu He, Weiye Chen, Yiqun Xie, Han Bao, Xun Zhou, Xiaowei Jia, Zhe Jiang, Rahul Ghosh, Praveen Ravirathinam

Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022

Fairness by "Where": A Statistically-Robust and Model-Agnostic Bi-level Learning Framework.

Yiqun Xie, Erhu He, Xiaowei Jia, Weiye Chen, Sergii Skakun, Han Bao, Zhe Jiang, Rahul Ghosh, Praveen Ravirathinam

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

A Statistically-Guided Deep Network Transformation and Moderation Framework for Data with Spatial Heterogeneity.

Yiqun Xie, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh, Praveen Ravirathinam

Proceedings of the IEEE International Conference on Data Mining, 2021