Physics Guided Machine Learning Methods for Hydrology

no code implementations • 2 Dec 2020 • Ankush Khandelwal, Shaoming Xu, Xiang Li, Xiaowei Jia, Michael Stienbach, Christopher Duffy, John Nieber, Vipin Kumar

The goal of this work is to incorporate our understanding of physical processes and constraints in hydrology into machine learning algorithms, and thus bridge the performance gap while reducing the need for large amounts of data compared to traditional data-driven approaches.

BIG-bench Machine Learning