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VI-PINNs: Variance-involved physics-informed neural networks for fast and accurate prediction of partial differential equations

Bin Shan, Ye Li, Sheng-Jun Huang

2025Neurocomputing11 citationsDOI

Topics & Concepts

Artificial neural networkVariance (accounting)Partial differential equationComputer scienceApplied mathematicsStatistical physicsMachine learningArtificial intelligenceMathematicsPhysicsMathematical analysisBusinessAccountingModel Reduction and Neural NetworksNuclear Engineering Thermal-HydraulicsFluid Dynamics and Turbulent Flows
VI-PINNs: Variance-involved physics-informed neural networks for fast and accurate prediction of partial differential equations | Litcius