| A statistically-guided deep network transformation and moderation framework for data with spatial heterogeneity Y Xie, E He, X Jia, H Bao, X Zhou, R Ghosh, P Ravirathinam 2021 IEEE International Conference on Data Mining (ICDM), 767-776, 2021 | 51 | 2021 |
| Fairness by “where”: A statistically-robust and model-agnostic bi-level learning framework Y Xie, E He, X Jia, W Chen, S Skakun, H Bao, Z Jiang, R Ghosh, ... Proceedings of the AAAI conference on artificial intelligence 36 (11), 12208 …, 2022 | 32 | 2022 |
| Physics guided neural networks for time-aware fairness: an application in crop yield prediction E He, Y Xie, L Liu, W Chen, Z Jin, X Jia Proceedings of the AAAI Conference on Artificial Intelligence 37 (12), 14223 …, 2023 | 27 | 2023 |
| Sailing in the location-based fairness-bias sphere E He, Y Xie, X Jia, W Chen, H Bao, X Zhou, Z Jiang, R Ghosh, ... Proceedings of the 30th international conference on advances in geographic …, 2022 | 19 | 2022 |
| Harnessing heterogeneity in space with statistically guided meta-learning Y Xie, W Chen, E He, X Jia, H Bao, X Zhou, R Ghosh, P Ravirathinam Knowledge and information systems 65 (6), 2699-2729, 2023 | 11 | 2023 |
| Entity aware modelling: A survey R Ghosh, H Yang, A Khandelwal, E He, A Renganathan, S Sharma, X Jia, ... arXiv preprint arXiv:2302.08406, 2023 | 7 | 2023 |
| Fair graph learning using constraint-aware priority adjustment and graph masking in river networks E He, Y Xie, A Sun, J Zwart, J Yang, Z Jin, Y Wang, H Karimi, X Jia Proceedings of the AAAI Conference on Artificial Intelligence 38 (20), 22087 …, 2024 | 4 | 2024 |
| Learning with location-based fairness: A statistically-robust framework and acceleration E He, Y Xie, W Chen, S Skakun, H Bao, R Ghosh, P Ravirathinam, X Jia IEEE Transactions on Knowledge and Data Engineering, 2024 | 4 | 2024 |
| Heterogeneity-aware deep learning in space: Performance and fairness Y Xie, X Jia, W Chen, E He Handbook of Geospatial Artificial Intelligence, 151-176, 2023 | 4 | 2023 |
| Knowledge guided machine learning for extracting, preserving, and adapting physics-aware features E He, Y Xie, L Liu, Z Jin, D Zhang, X Jia Proceedings of the 2024 SIAM International Conference on Data Mining (SDM …, 2024 | 3 | 2024 |
| Statistically-Guided Deep Network Transformation to Harness Heterogeneity in Space Y Xie, E He, X Jia, H Bao, X Zhou, R Ghosh, P Ravirathinam Proceedings of the Thirty-First International Joint Conference on Artificial …, 2022 | 3 | 2022 |
| Referee-meta-learning for fast adaptation of locational fairness W Chen, Y Xie, X Jia, E He, H Bao, B An, X Zhou Proceedings of the AAAI Conference on Artificial Intelligence 38 (20), 21949 …, 2024 | 2 | 2024 |
| Physics-Guided Fair Graph Sampling for Water Temperature Prediction in River Networks E He, D Kutscher, Y Xie, J Zwart, Z Jiang, H Yao, X Jia arXiv preprint arXiv:2412.16523, 2024 | | 2024 |
| PAIL: Performance based Adversarial Imitation Learning Engine for Carbon Neutral Optimization Y Ye, LA Tang, H Wang, R Yu, W Yu, E He, H Chen, H Xiong Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | | 2024 |
| 16 Deep Learning for Spatial W Chen, Y Xie, X Jia, E He Big Data: Techniques and Technologies in Geoinformatics, 254, 2024 | | 2024 |
| 18 Fairness-Aware Deep Learning in Space E He, W Chen, Y Xie, X Jia Big Data: Techniques and Technologies in Geoinformatics, 293, 2024 | | 2024 |
| CGS: coupled growth and survival model with cohort fairness E He, Y Wan, BH Letcher, JH Fair, Y Xie, X Jia International Joint Conferences on Artificial Intelligence Organization, 2023 | | 2023 |
| Advancing Sustainability in Global Supply Chains through Agent-based Simulation H Wang, E He, C Zheng, LA Tang, Z Chen, X Zhao, X Jia, H Chen | | |
| Fairness-Aware Deep Learning in Space E He, W Chen, Y Xie, X Jia Big Data, 293-315, 0 | | |
| Deep Learning for Spatial Data: Heterogeneity and Adaptation W Chen, Y Xie, X Jia, E He Big Data, 254-271, 0 | | |
Xiaowei JiaUniversity of PittsburghVerifisert e-postadresse på pitt.edu