Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles

Romit Maulik, Romain Egele, Krishnan Raghavan +1

Classical problems in computational physics such as data-driven forecasting and signal reconstruction from sparse sensors have recently seen an explosion in deep neural network (DN…