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An intelligent interface for integrating climate, hydrology, agriculture, and socioeconomic models., , , , , , , , , and 15 other author(s). IUI Companion, page 111-112. ACM, (2019)Physics Guided Machine Learning Methods for Hydrology., , , , , , , and . CoRR, (2020)Probabilistic Inverse Modeling: An Application in Hydrology., , , , , , , and . SDM, page 847-855. SIAM, (2023)An introduction to the special issue on Geoscience Papers of the Future, , , , and . Earth and Space Science, 3 (10): 441-444 (2016)Enhancing the performance of feature selection algorithms for classifying hyperspectral imagery., , and . IGARSS, page 3264-3267. IEEE, (2004)Hierarchically Disentangled Recurrent Network for Factorizing System Dynamics of Multi-scale Systems., , , , , , , , and . CoRR, (2024)Mini-Batch Learning Strategies for modeling long term temporal dependencies: A study in environmental applications., , , , , , , , , and 2 other author(s). SDM, page 649-657. SIAM, (2023)Robust Inverse Framework using Knowledge-guided Self-Supervised Learning: An application to Hydrology., , , , , , , , and . KDD, page 465-474. ACM, (2022)Uncertainty Quantification in Inverse Models in Hydrology., , , , , , , and . CoRR, (2023)A tightly coupled GIS and distributed hydrologic modeling framework., , and . Environ. Model. Softw., (2014)