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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 41–50 of 192 papers

TitleStatusHype
An analysis of Universal Differential Equations for data-driven discovery of Ordinary Differential EquationsCode0
A Physics-Augmented GraphGPS Framework for the Reconstruction of 3D Riemann Problems from Sparse DataCode0
Differentiable Neural-Integrated Meshfree Method for Forward and Inverse Modeling of Finite Strain HyperelasticityCode0
Hyperspectral Blind Unmixing using a Double Deep Image PriorCode0
Noise-aware Physics-informed Machine Learning for Robust PDE DiscoveryCode0
Kolmogorov n-Widths for Multitask Physics-Informed Machine Learning (PIML) Methods: Towards Robust MetricsCode0
A Statistical Evaluation of Indoor LoRaWAN Environment-Aware Propagation for 6G: MLR, ANOVA, and Residual Distribution AnalysisCode0
Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming abilityCode0
Physics-informed kernel learningCode0
Adapting Physics-Informed Neural Networks to Improve ODE Optimization in Mosquito Population DynamicsCode0
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