Scalable uncertainty quantification for deep operator networks using randomized priors
Yi-Bo Yang, Georgios Kissas, Paris Perdikaris
Topics & Concepts
Computer scienceUncertainty quantificationScalabilityInferenceFrequentist inferencePrior probabilityCode (set theory)Operator (biology)Function (biology)Data miningArtificial intelligenceMachine learningBayesian inferenceBayesian probabilityDatabaseEvolutionary biologyProgramming languageBiochemistryGeneRepressorChemistryTranscription factorSet (abstract data type)BiologyModel Reduction and Neural NetworksProbabilistic and Robust Engineering DesignAdversarial Robustness in Machine Learning