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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 121–130 of 192 papers

TitleStatusHype
Physics-informed machine learning of redox flow battery based on a two-dimensional unit cell model—0
Physics-Informed Computer Vision: A Review and Perspectives—0
Nearly Optimal VC-Dimension and Pseudo-Dimension Bounds for Deep Neural Network Derivatives—0
Unsupervised Discovery of Extreme Weather Events Using Universal Representations of Emergent OrganizationCode0
Π-ML: A dimensional analysis-based machine learning parameterization of optical turbulence in the atmospheric surface layerCode0
Physics-informed machine learning for moving load problems—0
A Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study—0
Viscoelastic Constitutive Artificial Neural Networks (vCANNs) - a framework for data-driven anisotropic nonlinear finite viscoelasticityCode0
Feature-adjacent multi-fidelity physics-informed machine learning for partial differential equations—0
Discrete-Time Nonlinear Feedback Linearization via Physics-Informed Machine Learning—0
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