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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 181–190 of 192 papers

TitleStatusHype
How important are activation functions in regression and classification? A survey, performance comparison, and future directions—0
Identifying Ordinary Differential Equations for Data-efficient Model-based Reinforcement Learning—0
Enhanced BPINN Training Convergence in Solving General and Multi-scale Elliptic PDEs with Noise—0
Inferring turbulent velocity and temperature fields and their statistics from Lagrangian velocity measurements using physics-informed Kolmogorov-Arnold Networks—0
KKANs: Kurkova-Kolmogorov-Arnold Networks and Their Learning Dynamics—0
Label Propagation Training Schemes for Physics-Informed Neural Networks and Gaussian Processes—0
(Un)supervised Learning of Maximal Lyapunov Functions—0
Learning ergodic averages in chaotic systems—0
Machine Learning with Physics Knowledge for Prediction: A Survey—0
MetaPhysiCa: OOD Robustness in Physics-informed Machine Learning—0
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