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CREST-iMAP v1.0: A fully coupled hydrologic-hydraulic modeling framework dedicated to flood inundation mapping and prediction.

, , , , , , , , , , , , and . Environ. Model. Softw., (2021)

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Enhancing understanding and improving prediction of severe weather through spatiotemporal relational learning., , , , and . Mach. Learn., 95 (1): 27-50 (2014)Creating significant learning experiences in introductory artificial intelligence., and . SIGCSE, page 39-43. ACM, (2007)Steerable Clustering for Visual Analysis of Ecosystems., , , and . EuroVA@EuroVis, Eurographics Association, (2011)Spatiotemporal Relational Probability Trees: An Introduction., , , , and . ICDM, page 935-940. IEEE Computer Society, (2008)Machine learning enhancement of Storm Scale Ensemble precipitation forecasts., , and . CIDU, page 39-46. IEEE, (2012)Welcome to AI matters, volume 3, issue 4., and . AI Matters, 3 (4): 3 (2018)Using the XSEDE supercomputing and visualization resources to improve tornado prediction using data mining., , , and . XSEDE, page 35:1-35:2. ACM, (2012)Making in-class competitions desirable for marginalized groups., and . FIE, page 704-706. IEEE Computer Society, (2013)Report on the NSF Workshop on Sustainable Computing for Sustainability (NSF WSCS 2024)., , and . CoRR, (2024)Learning ensembles of Continuous Bayesian Networks: An application to rainfall prediction., , and . CIDU, page 112-117. IEEE, (2012)