| Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems J Willard, X Jia, S Xu, M Steinbach, V Kumar ACM Computing Surveys, 2022 | 853* | 2022 |
| Process‐guided deep learning predictions of lake water temperature JS Read, X Jia, J Willard, AP Appling, JA Zwart, SK Oliver, A Karpatne, ... Water Resources Research 55 (11), 9173-9190, 2019 | 303 | 2019 |
| Physics guided RNNs for modeling dynamical systems: A case study in simulating lake temperature profiles X Jia, J Willard, A Karpatne, J Read, J Zwart, M Steinbach, V Kumar Proceedings of the 2019 SIAM international conference on data mining, 558-566, 2019 | 284 | 2019 |
| Physics-guided machine learning for scientific discovery: An application in simulating lake temperature profiles X Jia, J Willard, A Karpatne, JS Read, JA Zwart, M Steinbach, V Kumar ACM/IMS Transactions on Data Science 2 (3), 1-26, 2021 | 247 | 2021 |
| Physics-guided recurrent graph model for predicting flow and temperature in river networks X Jia, J Zwart, J Sadler, A Appling, S Oliver, S Markstrom, J Willard, S Xu, ... Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021 | 72 | 2021 |
| Predicting water temperature dynamics of unmonitored lakes with meta‐transfer learning JD Willard, JS Read, AP Appling, SK Oliver, X Jia, V Kumar Water Resources Research 57 (7), e2021WR029579, 2021 | 66 | 2021 |
| Physics guided recurrent neural networks for modeling dynamical systems: Application to monitoring water temperature and quality in lakes X Jia, A Karpatne, J Willard, M Steinbach, J Read, PC Hanson, HA Dugan, ... arXiv preprint arXiv:1810.02880, 2018 | 59 | 2018 |
| Can machine learning accelerate process understanding and decision‐relevant predictions of river water quality? C Varadharajan, AP Appling, B Arora, DS Christianson, VC Hendrix, ... Hydrological Processes 36 (4), e14565, 2022 | 39 | 2022 |
| Integrating physics-based modeling with machine learning: A survey. arXiv J Willard, X Jia, S Xu, M Steinbach, V Kumar arXiv preprint arXiv:2003.04919, 2020 | 22 | 2020 |
| Daily surface temperatures for 185,549 lakes in the conterminous United States estimated using deep learning (1980–2020) JD Willard, JS Read, S Topp, GJA Hansen, V Kumar Limnology and Oceanography Letters 7 (4), 287-301, 2022 | 19 | 2022 |
| Physics-guided recurrent graph networks for predicting flow and temperature in river networks X Jia, J Zwart, J Sadler, A Appling, S Oliver, S Markstrom, J Willard, S Xu, ... arXiv preprint arXiv:2009.12575, 2020 | 19 | 2020 |
| Stream temperature predictions for river basin management in the Pacific Northwest and mid-Atlantic regions using machine learning H Weierbach, AR Lima, JD Willard, VC Hendrix, DS Christianson, ... Water 14 (7), 1032, 2022 | 17 | 2022 |
| Integrating scientific knowledge with machine learning for engineering and environmental systems. arXiv 2020 J Willard, X Jia, S Xu, M Steinbach, V Kumar arXiv preprint arXiv:2003.04919, 2003 | 13 | 2003 |
| Invertibility aware integration of static and time-series data: An application to lake temperature modeling K Tayal, X Jia, R Ghosh, J Willard, J Read, V Kumar Proceedings of the 2022 SIAM international conference on data mining (SDM …, 2022 | 8 | 2022 |
| Time series predictions in unmonitored sites: A survey of machine learning techniques in water resources JD Willard, C Varadharajan, X Jia, V Kumar arXiv preprint arXiv:2308.09766, 2023 | 4 | 2023 |
| Mini-Batch Learning Strategies for modeling long term temporal dependencies: a study in environmental applications S Xu, A Khandelwal, X Li, X Jia, L Liu, J Willard, R Ghosh, K Cutler, ... Proceedings of the 2023 SIAM International Conference on Data Mining (SDM …, 2023 | 4 | 2023 |
| Data release: Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning J Willard, J Read, A Appling, S Oliver U.S. Geological Survey data release, https://doi.org/10.5066/P9I00WFR, 2021 | 3 | 2021 |
| Using machine learning to develop a predictive understanding of the impacts of extreme water cycle perturbations on river water quality C Varadharajan, V Kumar, J Willard, J Zwart, J Sadler, H Weierbach, ... Lawrence Berkeley National Lab.(LBNL), Berkeley, CA (United States); Univ …, 2021 | 3 | 2021 |
| Physics guided recurrent neural networks for modeling dynamical systems: Application to monitoring water temperature and quality in lakes. arXiv, 1810.02880 X Jia, A Karpatne, J Willard, M Steinbach, J Read, PC Hanson, HA Dugan, ... arXiv preprint arXiv:1810.02880, 2018 | 3 | 2018 |
| Dataset for'Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning', Water 2022 H Weierbach, AR Lima, JD Willard, VC Hendrix, DS Christianson, ... Environmental System Science Data Infrastructure for a Virtual Ecosystem …, 2022 | 2 | 2022 |
Vipin KumarUniversity of Minnesota在 umn.edu 的电子邮件经过验证
