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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 51–60 of 192 papers

TitleStatusHype
A Statistical Evaluation of Indoor LoRaWAN Environment-Aware Propagation for 6G: MLR, ANOVA, and Residual Distribution AnalysisCode0
Kolmogorov n-Widths for Multitask Physics-Informed Machine Learning (PIML) Methods: Towards Robust MetricsCode0
Estimating irregular water demands with physics-informed machine learning to inform leakage detectionCode0
Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming abilityCode0
A Machine Learning Pressure Emulator for Hydrogen EmbrittlementCode0
Adapting Physics-Informed Neural Networks to Improve ODE Optimization in Mosquito Population DynamicsCode0
Hyperspectral Blind Unmixing using a Double Deep Image PriorCode0
LaPON: A Lagrange's-mean-value-theorem-inspired operator network for solving PDEs and its application on NSECode0
Neural modal ordinary differential equations: Integrating physics-based modeling with neural ordinary differential equations for modeling high-dimensional monitored structuresCode0
Physics-informed machine learning as a kernel methodCode0
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