A Statistically-Guided Deep Network Transformation and Moderation Framework for Data with Spatial Heterogeneity. - Yiqun Xie; Erhu He; Xiaowei Jia; Han Bao 003; Xun Zhou 001; Rahul Ghosh; Praveen Ravirathinam (ICDM, 2021)

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 003; Zhe Jiang 001; Rahul Ghosh; Praveen Ravirathinam (AAAI, 2022)

Sailing in the location-based fairness-bias sphere. - Erhu He; Weiye Chen; Yiqun Xie; Han Bao 003; Xun Zhou 001; Xiaowei Jia; Zhe Jiang 001; Rahul Ghosh; Praveen Ravirathinam (SIGSPATIAL/GIS, 2022)

Statistically-Guided Deep Network Transformation to Harness Heterogeneity in Space (Extended Abstract). - Yiqun Xie; Erhu He; Xiaowei Jia; Han Bao 003; Xun Zhou 001; Rahul Ghosh; Praveen Ravirathinam (IJCAI, 2022)

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 (AAAI, 2023)

CGS: Coupled Growth and Survival Model with Cohort Fairness. - Erhu He; Yue Wan; Benjamin H. Letcher; Jennifer H. Fair; Yiqun Xie; Xiaowei Jia (IJCAI, 2023)

Entity Aware Modelling: A Survey. - Rahul Ghosh; Haoyu Yang; Ankush Khandelwal; Erhu He; Arvind Renganathan; Somya Sharma; Xiaowei Jia; Vipin Kumar 001 (CoRR, 2023)

Harnessing heterogeneity in space with statistically guided meta-learning. - Yiqun Xie; Weiye Chen; Erhu He; Xiaowei Jia; Han Bao 003; Xun Zhou 001; Rahul Ghosh; Praveen Ravirathinam (Knowl. Inf. Syst., 2023)

Referee-Meta-Learning for Fast Adaptation of Locational Fairness. - Weiye Chen; Yiqun Xie; Xiaowei Jia; Erhu He; Han Bao 003; Bang An 002; Xun Zhou 001 (AAAI, 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 070; Zhenong Jin; Yang Wang; Hassan A. Karimi; Xiaowei Jia (AAAI, 2024)

PAIL: Performance based Adversarial Imitation Learning Engine for Carbon Neutral Optimization. - Yuyang Ye 002; Lu-An Tang; Haoyu Wang 003; Runlong Yu; Wenchao Yu; Erhu He; Haifeng Chen; Hui Xiong 001 (KDD, 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 (SDM, 2024)

Learning With Location-Based Fairness: A Statistically-Robust Framework and Acceleration. - Erhu He; Yiqun Xie; Weiye Chen; Sergii Skakun; Han Bao 003; Rahul Ghosh; Praveen Ravirathinam; Xiaowei Jia (IEEE Trans. Knowl. Data Eng., 2024)

Physics-Guided Fair Graph Sampling for Water Temperature Prediction in River Networks. - Erhu He; Declan Kutscher; Yiqun Xie; Jacob Zwart; Zhe Jiang 001; Huaxiu Yao; Xiaowei Jia (AAAI, 2025)