Theory-guided data science: A new paradigm for scientific discovery from data A Karpatne, G Atluri, JH Faghmous, M Steinbach, A Banerjee, A Ganguly, ... IEEE Transactions on knowledge and data engineering 29 (10), 2318-2331, 2017 | 1352 | 2017 |
Physics-guided neural networks (pgnn): An application in lake temperature modeling A Daw, A Karpatne, WD Watkins, JS Read, V Kumar Knowledge Guided Machine Learning, 353-372, 2022 | 839 | 2022 |
Spatio-temporal data mining: A survey of problems and methods G Atluri, A Karpatne, V Kumar ACM Computing Surveys (CSUR) 51 (4), 1-41, 2018 | 586 | 2018 |
Machine learning for the geosciences: Challenges and opportunities A Karpatne, I Ebert-Uphoff, S Ravela, HA Babaie, V Kumar IEEE Transactions on Knowledge and Data Engineering 31 (8), 1544-1554, 2018 | 546 | 2018 |
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 | 317 | 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 | 300 | 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 | 274 | 2021 |
Incorporating prior domain knowledge into deep neural networks N Muralidhar, MR Islam, M Marwah, A Karpatne, N Ramakrishnan 2018 IEEE international conference on big data (big data), 36-45, 2018 | 211 | 2018 |
BHPMF–a hierarchical B ayesian approach to gap‐filling and trait prediction for macroecology and functional biogeography F Schrodt, J Kattge, H Shan, F Fazayeli, J Joswig, A Banerjee, ... Global Ecology and Biogeography 24 (12), 1510-1521, 2015 | 187 | 2015 |
An approach for global monitoring of surface water extent variations in reservoirs using MODIS data A Khandelwal, A Karpatne, ME Marlier, J Kim, DP Lettenmaier, V Kumar Remote sensing of Environment 202, 113-128, 2017 | 182 | 2017 |
Physics-guided architecture (pga) of neural networks for quantifying uncertainty in lake temperature modeling A Daw, RQ Thomas, CC Carey, JS Read, AP Appling, A Karpatne Proceedings of the 2020 siam international conference on data mining, 532-540, 2020 | 166 | 2020 |
Mitigating propagation failures in physics-informed neural networks using retain-resample-release (r3) sampling A Daw, J Bu, S Wang, P Perdikaris, A Karpatne arXiv preprint arXiv:2207.02338, 2022 | 137* | 2022 |
Monitoring land-cover changes: A machine-learning perspective A Karpatne, Z Jiang, RR Vatsavai, S Shekhar, V Kumar IEEE Geoscience and Remote Sensing Magazine 4 (2), 8-21, 2016 | 113 | 2016 |
Global monitoring of inland water dynamics: State-of-the-art, challenges, and opportunities A Karpatne, A Khandelwal, X Chen, V Mithal, J Faghmous, V Kumar Computational sustainability, 121-147, 2016 | 102 | 2016 |
Predicting lake surface water phosphorus dynamics using process-guided machine learning PC Hanson, AB Stillman, X Jia, A Karpatne, HA Dugan, CC Carey, ... Ecological Modelling 430, 109136, 2020 | 87 | 2020 |
Gcnnmatch: Graph convolutional neural networks for multi-object tracking via sinkhorn normalization I Papakis, A Sarkar, A Karpatne arXiv preprint arXiv:2010.00067, 2020 | 74 | 2020 |
Phynet: Physics guided neural networks for particle drag force prediction in assembly N Muralidhar, J Bu, Z Cao, L He, N Ramakrishnan, D Tafti, A Karpatne Proceedings of the 2020 SIAM international conference on data mining, 559-567, 2020 | 62 | 2020 |
Knowledge guided machine learning: Accelerating discovery using scientific knowledge and data A Karpatne, R Kannan, V Kumar CRC Press, 2022 | 60 | 2022 |
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 | 60 | 2018 |
Quadratic residual networks: A new class of neural networks for solving forward and inverse problems in physics involving pdes J Bu, A Karpatne Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021 | 58 | 2021 |