GAN-Based Priors for Quantifying Uncertainty in Supervised Learning

Abstract

Related DatabasesWeb of Science You must be logged in with an active subscription to view this.Article DataHistorySubmitted: 20 July 2020Accepted: 29 June 2021Published online: 30 September 2021Keywordsuncertainty quantification, Bayesian inference, machine learning, generative adversarial network (GAN), model order reduction, active learning, Markov Chain Monte Carlo (MCMC), Hamiltonian Monte Carlo (HMC)AMS Subject Headings62F15, 68T37, 68T07, 6204Publication DataISSN (online): 2166-2525Publisher: Society for Industrial and Applied MathematicsCODEN: sjuqa3