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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 51–75 of 192 papers

TitleStatusHype
Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin ModelsCode0
PDE-DKL: PDE-constrained deep kernel learning in high dimensionalityCode0
Estimating irregular water demands with physics-informed machine learning to inform leakage detectionCode0
Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming abilityCode0
Physics-Informed Calibration of Aeromagnetic Compensation in Magnetic Navigation Systems using Liquid Time-Constant NetworksCode0
Viscoelastic Constitutive Artificial Neural Networks (vCANNs) - a framework for data-driven anisotropic nonlinear finite viscoelasticityCode0
Physics-informed kernel learningCode0
Neural oscillators for generalization of physics-informed machine learningCode0
Neural modal ordinary differential equations: Integrating physics-based modeling with neural ordinary differential equations for modeling high-dimensional monitored structuresCode0
Noise-aware Physics-informed Machine Learning for Robust PDE DiscoveryCode0
L-HYDRA: Multi-Head Physics-Informed Neural NetworksCode0
Adapting Physics-Informed Neural Networks to Improve ODE Optimization in Mosquito Population DynamicsCode0
LaPON: A Lagrange's-mean-value-theorem-inspired operator network for solving PDEs and its application on NSECode0
Physics-informed machine learning as a kernel methodCode0
From PINNs to PIKANs: Recent Advances in Physics-Informed Machine Learning—0
Fourier-Invertible Neural Encoder (FINE) for Homogeneous Flows—0
FMEnets: Flow, Material, and Energy networks for non-ideal plug flow reactor design—0
A Physics-informed machine learning model for time-dependent wave runup prediction—0
A Mechanism-Learning Deeply Coupled Model for Remote Sensing Retrieval of Global Land Surface Temperature—0
Filtered Partial Differential Equations: a robust surrogate constraint in physics-informed deep learning framework—0
A physics-informed machine learning model for reconstruction of dynamic loads—0
Feature-adjacent multi-fidelity physics-informed machine learning for partial differential equations—0
Neural Operator: Is data all you need to model the world? An insight into the impact of Physics Informed Machine Learning—0
A Physics-Informed Machine Learning Model for Porosity Analysis in Laser Powder Bed Fusion Additive Manufacturing—0
A Critical Review of Physics-Informed Machine Learning Applications in Subsurface Energy Systems—0
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