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
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
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
Physics-guided neural networks (pgnn): An application in lake temperature modeling
A Karpatne, W Watkins, J Read, V Kumar
arXiv preprint arXiv:1710.11431, 2017
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
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
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
Twin support vector regression for the simultaneous learning of a function and its derivatives
R Khemchandani, A Karpatne, S Chandra
International Journal of Machine Learning and Cybernetics 4 (1), 51-63, 2013
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
Proximal support tensor machines
R Khemchandani, A Karpatne, S Chandra
International Journal of Machine Learning and Cybernetics 4 (6), 703-712, 2013
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
Predictive Learning in the Presence of Heterogeneity and Limited Training Data
A Karpatne, A Khandelwal, S Boriah, V Kumar
SDM, 253-261, 2014
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
Symmetry breaking in the congest model: Time-and message-efficient algorithms for ruling sets
S Pai, G Pandurangan, SV Pemmaraju, T Riaz, P Robinson
arXiv preprint arXiv:1705.07861, 2017
Generalized eigenvalue proximal support vector regressor
R Khemchandani, A Karpatne, S Chandra
Expert Systems with Applications 38 (10), 13136-13142, 2011
Ensemble learning methods for binary classification with multi-modality within the classes
A Karpatne, A Khandelwal, V Kumar
SIAM International Conference on Data Mining (SDM), 730-738, 2015
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
A new data mining framework for forest fire mapping
XC Chen, A Karpatne, Y Chamber, V Mithal, M Lau, K Steinhaeuser, ...
2012 Conference on Intelligent Data Understanding, 104-111, 2012
Tripoles: A new class of relationships in time series data
S Agrawal, G Atluri, A Karpatne, W Haltom, S Liess, S Chatterjee, ...
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017
Importance of vegetation type in forest cover estimation
A Karpatne, M Blank, M Lau, S Boriah, K Steinhaeuser, M Steinbach, ...
2012 Conference on Intelligent Data Understanding, 71-78, 2012
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