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Physics-informed machine learning

Machine learning used to represent physics-based and/or engineering models

Papers

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Showing 1–10 of 192 papers

TitleStatusHype
NeuralFoil: An Airfoil Aerodynamics Analysis Tool Using Physics-Informed Machine LearningCode3
Fully-fused Multi-Layer Perceptrons on Intel Data Center GPUsCode2
Non-destructive Degradation Pattern Decoupling for Ultra-early Battery Prototype Verification Using Physics-informed Machine LearningCode2
Physics-Informed Machine Learning: A Survey on Problems, Methods and ApplicationsCode2
Adaptive Training of Grid-Dependent Physics-Informed Kolmogorov-Arnold NetworksCode2
Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systemsCode1
Multi-Objective Loss Balancing for Physics-Informed Deep LearningCode1
Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaicsCode1
Finite Operator Learning: Bridging Neural Operators and Numerical Methods for Efficient Parametric Solution and Optimization of PDEsCode1
Analyzing Koopman approaches to physics-informed machine learning for long-term sea-surface temperature forecastingCode1
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