Anuj Karpatne
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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
Physics-guided neural networks (pgnn): An application in lake temperature modeling
A Daw, A Karpatne, W Watkins, J Read, V Kumar
arXiv preprint arXiv:1710.11431, 2017
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
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
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
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
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
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
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
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
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
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
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
Gcnnmatch: Graph convolutional neural networks for multi-object tracking via sinkhorn normalization
I Papakis, A Sarkar, A Karpatne
arXiv preprint arXiv:2010.00067, 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
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
A vision for the development of benchmarks to bridge geoscience and data science
I Ebert-Uphoff, DR Thompson, I Demir, YR Gel, A Karpatne, M Guereque, ...
17th International Workshop on Climate Informatics, 2017
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
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
Predictive Learning in the Presence of Heterogeneity and Limited Training Data
A Karpatne, A Khandelwal, S Boriah, V Kumar
SDM, 253-261, 2014
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