Erhu He

17 papers A* 9A 1Journal 6Unranked 1
YearRankTypeTitle / Venue / Authors
2025 A* conf
Physics-Guided Fair Graph Sampling for Water Temperature Prediction in River Networks.
AAAI
Erhu He, Declan Kutscher, Yiqun Xie, Jacob Zwart, Zhe Jiang, Huaxiu Yao, Xiaowei Jia
2024 A* conf
Fair Graph Learning Using Constraint-Aware Priority Adjustment and Graph Masking in River Networks.
AAAI
Erhu He, Yiqun Xie, Alexander Y. Sun, Jacob Zwart, Jie Yang, Zhenong Jin, Yang Wang, Hassan A. Karimi, Xiaowei Jia
2024 A conf
Knowledge Guided Machine Learning for Extracting, Preserving, and Adapting Physics-aware Features.
SDM
Erhu He, Yiqun Xie, Licheng Liu, Zhenong Jin, Dajun Zhang, Xiaowei Jia
2024 J jnl
Learning With Location-Based Fairness: A Statistically-Robust Framework and Acceleration.
IEEE Trans. Knowl. Data Eng.
Erhu He, Yiqun Xie, Weiye Chen, Sergii Skakun, Han Bao, Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia
2024 A* conf
PAIL: Performance based Adversarial Imitation Learning Engine for Carbon Neutral Optimization.
KDD
Yuyang Ye, Lu-An Tang, Haoyu Wang, Runlong Yu, Wenchao Yu, Erhu He, Haifeng Chen, Hui Xiong
2024 J jnl
PAIL: Performance based Adversarial Imitation Learning Engine for Carbon Neutral Optimization.
CoRR
Yuyang Ye, Lu-An Tang, Haoyu Wang, Runlong Yu, Wenchao Yu, Erhu He, Haifeng Chen, Hui Xiong
2024 J jnl
Physics-Guided Fair Graph Sampling for Water Temperature Prediction in River Networks.
CoRR
Erhu He, Declan Kutscher, Yiqun Xie, Jacob Zwart, Zhe Jiang, Huaxiu Yao, Xiaowei Jia
2024 A* conf
Referee-Meta-Learning for Fast Adaptation of Locational Fairness.
AAAI
Weiye Chen, Yiqun Xie, Xiaowei Jia, Erhu He, Han Bao, Bang An, Xun Zhou
2024 J jnl
Referee-Meta-Learning for Fast Adaptation of Locational Fairness.
CoRR
Weiye Chen, Yiqun Xie, Xiaowei Jia, Erhu He, Han Bao, Bang An, Xun Zhou
2023 A* conf
CGS: Coupled Growth and Survival Model with Cohort Fairness.
IJCAI
Erhu He, Yue Wan, Benjamin H. Letcher, Jennifer H. Fair, Yiqun Xie, Xiaowei Jia
2023 J jnl
Entity Aware Modelling: A Survey.
CoRR
Rahul Ghosh, Haoyu Yang, Ankush Khandelwal, Erhu He, Arvind Renganathan, Somya Sharma, Xiaowei Jia, Vipin Kumar
2023 J jnl
Harnessing heterogeneity in space with statistically guided meta-learning.
Knowl. Inf. Syst.
Yiqun Xie, Weiye Chen, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh, Praveen Ravirathinam
2023 A* conf
Physics Guided Neural Networks for Time-Aware Fairness: An Application in Crop Yield Prediction.
AAAI
Erhu He, Yiqun Xie, Licheng Liu, Weiye Chen, Zhenong Jin, Xiaowei Jia
2022 A* conf
Fairness by "Where": A Statistically-Robust and Model-Agnostic Bi-level Learning Framework.
AAAI
Yiqun Xie, Erhu He, Xiaowei Jia, Weiye Chen, Sergii Skakun, Han Bao, Zhe Jiang, Rahul Ghosh, Praveen Ravirathinam
2022 — conf
Sailing in the location-based fairness-bias sphere.
SIGSPATIAL/GIS
Erhu He, Weiye Chen, Yiqun Xie, Han Bao, Xun Zhou, Xiaowei Jia, Zhe Jiang, Rahul Ghosh, Praveen Ravirathinam
2022 A* conf
Statistically-Guided Deep Network Transformation to Harness Heterogeneity in Space (Extended Abstract).
IJCAI
Yiqun Xie, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh, Praveen Ravirathinam
2021 A* conf
A Statistically-Guided Deep Network Transformation and Moderation Framework for Data with Spatial Heterogeneity.
ICDM
Yiqun Xie, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh, Praveen Ravirathinam