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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 71–80 of 192 papers

TitleStatusHype
Differentiable Predictive Control for Large-Scale Urban Road Networks—0
Adapting Physics-Informed Neural Networks to Improve ODE Optimization in Mosquito Population DynamicsCode0
A comprehensive and FAIR comparison between MLP and KAN representations for differential equations and operator networks—0
Non-destructive Degradation Pattern Decoupling for Ultra-early Battery Prototype Verification Using Physics-informed Machine LearningCode2
Physics-Informed Machine Learning On Polar Ice: A Survey—0
Physics-informed Discretization-independent Deep Compositional Operator NetworkCode0
Data-driven AC Optimal Power Flow with Physics-informed Learning and Calibrations—0
Label Propagation Training Schemes for Physics-Informed Neural Networks and Gaussian Processes—0
Fully-fused Multi-Layer Perceptrons on Intel Data Center GPUsCode2
Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming abilityCode0
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