Litcius/Paper detail

Multifidelity deep operator networks for data-driven and physics-informed problems

Amanda A. Howard, Mauro Perego, George Em Karniadakis, Panos Stinis

2023Journal of Computational Physics63 citationsDOIOpen Access PDF

Topics & Concepts

FidelityOperator (biology)High fidelityComputer scienceDeep learningArtificial intelligenceMachine learningPhysicsTranscription factorRepressorBiochemistryGeneTelecommunicationsAcousticsChemistryModel Reduction and Neural NetworksFluid Dynamics and Vibration AnalysisNuclear Engineering Thermal-Hydraulics
Multifidelity deep operator networks for data-driven and physics-informed problems | Litcius