| 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 | 166 | 2017 |
| 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, 2017 | 166 | 2017 |
| High spatiotemporal resolution of river planform dynamics from Landsat: The RivMAP toolbox and results from the Ucayali River J Schwenk, A Khandelwal, M Fratkin, V Kumar, E Foufoula‐Georgiou Earth and Space Science 4 (2), 46-75, 2017 | 117 | 2017 |
| 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 | 91 | 2016 |
| Incremental Dual-memory LSTM in Land Cover Prediction X Jia, A Khandelwal, G Nayak, J Gerber, K Carlson, P West, V Kumar Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017 | 80 | 2017 |
| Physics Guided Machine Learning Methods for Hydrology A Khandelwal, S Xu, X Li, X Jia, M Stienbach, C Duffy, J Nieber, V Kumar arXiv preprint arXiv:2012.02854, 2020 | 48 | 2020 |
| Mapping Burned Areas in Tropical Forests Using a Novel Machine Learning Framework V Mithal, G Nayak, A Khandelwal, V Kumar, R Nemani, NC Oza Remote Sensing 10 (1), 69, 2018 | 41 | 2018 |
| Satellite-based remote sensing data set of global surface water storage change from 1992 to 2018 R Tortini, N Noujdina, S Yeo, M Ricko, CM Birkett, A Khandelwal, V Kumar, ... Earth System Science Data 12 (2), 1141-1151, 2020 | 38 | 2020 |
| Predictive learning in the presence of heterogeneity and limited training data A Karpatne, A Khandelwal, S Boriah, V Kumar Proceedings of the 2014 SIAM International Conference on Data Mining, 253-261, 2014 | 38 | 2014 |
| Artificial intelligence for modeling complex systems: taming the complexity of expert models to improve decision making Y Gil, D Garijo, D Khider, CA Knoblock, V Ratnakar, M Osorio, H Vargas, ... ACM Transactions on Interactive Intelligent Systems 11 (2), 1-49, 2021 | 31 | 2021 |
| Predict land covers with transition modeling and incremental learning X Jia, A Khandelwal, G Nayak, J Gerber, K Carlson, P West, V Kumar Proceedings of the 2017 SIAM International Conference on Data Mining, 171-179, 2017 | 30 | 2017 |
| Post Classification Label Refinement Using Implicit Ordering Constraint Among Data Instances A Khandelwal, V Mithal, V Kumar Data Mining (ICDM), 2015 IEEE International Conference on, 799-804, 2015 | 29 | 2015 |
| Bringing automated, remote‐sensed, machine learning methods to monitoring crop landscapes at scale X Jia, A Khandelwal, DJ Mulla, PG Pardey, V Kumar Agricultural Economics 50, 41-50, 2019 | 28 | 2019 |
| Spatial Context-Aware Networks for Mining Temporal Discriminative Period in Land Cover Detection X Jia, S Li, A Khandelwal, G Nayak, A Karpatne, V Kumar Proceedings of the 2019 SIAM International Conference on Data Mining, 513-521, 2019 | 27 | 2019 |
| Learning large-scale plantation mapping from imperfect annotators X Jia, A Khandelwal, J Gerber, K Carlson, P West, V Kumar 2016 IEEE International Conference on Big Data (Big Data), 1192-1201, 2016 | 26 | 2016 |
| RAPT: Rare Class Prediction in Absence of True Labels V Mithal, G Nayak, A Khandelwal, V Kumar, NC Oza, R Nemani IEEE Transactions on Knowledge and Data Engineering 29 (11), 2484-2497, 2017 | 25 | 2017 |
| Clustering dynamic spatio-temporal patterns in the presence of noise and missing data XC Chen, JH Faghmous, A Khandelwal, V Kumar International Joint Conference on Artificial Intelligence, 2575-2581, 2015 | 25 | 2015 |
| ReaLSAT, a global dataset of reservoir and lake surface area variations A Khandelwal, A Karpatne, P Ravirathinam, R Ghosh, Z Wei, HA Dugan, ... Scientific Data 9 (1), 1-12, 2022 | 23 | 2022 |
| Sparse Gaussian Markov Random Field Mixtures for Anomaly Detection T Idé, A Khandelwal, J Kalagnanam Data Mining (ICDM), 2016 IEEE 16th International Conference on, 955-960, 2016 | 21 | 2016 |
| Regionalization in a global hydrologic deep learning model: from physical descriptors to random vectors X Li, A Khandelwal, X Jia, K Cutler, R Ghosh, A Renganathan, S Xu, ... Water Resources Research 58 (8), e2021WR031794, 2022 | 20 | 2022 |
Vipin KumarUniversity of MinnesotaDirección de correo verificada de umn.edu
