GAN-Based Priors for Quantifying Uncertainty in Supervised Learning
Dhruv Patel, Assad A. Oberai
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
Topics & Concepts
Markov chain Monte CarloPrior probabilityComputer scienceMachine learningArtificial intelligenceBayesian inferenceInferenceMonte Carlo methodBayesian probabilityBayesian networkMathematicsStatisticsFault Detection and Control SystemsMachine Learning and AlgorithmsGaussian Processes and Bayesian Inference