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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 101–110 of 192 papers

TitleStatusHype
Discovering Artificial Viscosity Models for Discontinuous Galerkin Approximation of Conservation Laws using Physics-Informed Machine Learning—0
Replication Study: Enhancing Hydrological Modeling with Physics-Guided Machine Learning—0
Kolmogorov n-Widths for Multitask Physics-Informed Machine Learning (PIML) Methods: Towards Robust MetricsCode0
Physics-informed machine learning as a kernel methodCode0
A Review of Physics-Informed Machine Learning Methods with Applications to Condition Monitoring and Anomaly Detection—0
Physics-Informed Calibration of Aeromagnetic Compensation in Magnetic Navigation Systems using Liquid Time-Constant NetworksCode0
A Physics-informed machine learning model for time-dependent wave runup prediction—0
A Comparative Evaluation of Additive Separability Tests for Physics-Informed Machine Learning—0
Randomized Physics-Informed Machine Learning for Uncertainty Quantification in High-Dimensional Inverse Problems—0
Value Approximation for Two-Player General-Sum Differential Games with State ConstraintsCode0
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