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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 26–50 of 192 papers

TitleStatusHype
A Machine Learning Pressure Emulator for Hydrogen EmbrittlementCode0
Physics-informed machine learning techniques for edge plasma turbulence modelling in computational theory and experimentCode0
Physics-Informed Machine Learning Method for Large-Scale Data Assimilation ProblemsCode0
Physics-informed machine learning for the COVID-19 pandemic: Adherence to social distancing and short-term predictions for eight countriesCode0
Physics-informed machine learning as a kernel methodCode0
DSSRNN: Decomposition-Enhanced State-Space Recurrent Neural Network for Time-Series AnalysisCode0
Physics-Informed Calibration of Aeromagnetic Compensation in Magnetic Navigation Systems using Liquid Time-Constant NetworksCode0
Physics-Informed Deep Neural Networks for Transient Electromagnetic AnalysisCode0
Non-overlapping, Schwarz-type Domain Decomposition Method for Physics and Equality Constrained Artificial Neural NetworksCode0
Neural oscillators for generalization of physics-informed machine learningCode0
PDE-DKL: PDE-constrained deep kernel learning in high dimensionalityCode0
Deep Learning Evidence for Global Optimality of Gerver's SofaCode0
L-HYDRA: Multi-Head Physics-Informed Neural NetworksCode0
Neural modal ordinary differential equations: Integrating physics-based modeling with neural ordinary differential equations for modeling high-dimensional monitored structuresCode0
Towards Size-Independent Generalization Bounds for Deep Operator NetsCode0
An analysis of Universal Differential Equations for data-driven discovery of Ordinary Differential EquationsCode0
A Physics-Augmented GraphGPS Framework for the Reconstruction of 3D Riemann Problems from Sparse DataCode0
Differentiable Neural-Integrated Meshfree Method for Forward and Inverse Modeling of Finite Strain HyperelasticityCode0
Hyperspectral Blind Unmixing using a Double Deep Image PriorCode0
Noise-aware Physics-informed Machine Learning for Robust PDE DiscoveryCode0
Kolmogorov n-Widths for Multitask Physics-Informed Machine Learning (PIML) Methods: Towards Robust MetricsCode0
A Statistical Evaluation of Indoor LoRaWAN Environment-Aware Propagation for 6G: MLR, ANOVA, and Residual Distribution AnalysisCode0
Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming abilityCode0
Physics-informed kernel learningCode0
Adapting Physics-Informed Neural Networks to Improve ODE Optimization in Mosquito Population DynamicsCode0
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