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Physics-informed machine learning

Machine learning used to represent physics-based and/or engineering models

Papers

Showing 150 of 192 papers

TitleStatusHype
NeuralFoil: An Airfoil Aerodynamics Analysis Tool Using Physics-Informed Machine LearningCode3
Fully-fused Multi-Layer Perceptrons on Intel Data Center GPUsCode2
Physics-Informed Machine Learning: A Survey on Problems, Methods and ApplicationsCode2
Non-destructive Degradation Pattern Decoupling for Ultra-early Battery Prototype Verification Using Physics-informed Machine LearningCode2
Adaptive Training of Grid-Dependent Physics-Informed Kolmogorov-Arnold NetworksCode2
Physics informed machine learning with Smoothed Particle Hydrodynamics: Hierarchy of reduced Lagrangian models of turbulenceCode1
Physics-informed neural networks for corrosion-fatigue prognosisCode1
Physics-informed machine learning with differentiable programming for heterogeneous underground reservoir pressure managementCode1
Social Physics Informed Diffusion Model for Crowd SimulationCode1
A Gaussian Process Framework for Solving Forward and Inverse Problems Involving Nonlinear Partial Differential EquationsCode1
Analyzing Koopman approaches to physics-informed machine learning for long-term sea-surface temperature forecastingCode1
A physics-informed neural network for wind turbine main bearing fatigueCode1
Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systemsCode1
Physics-Informed Machine Learning Simulator for Wildfire PropagationCode1
Fleet Prognosis with Physics-informed Recurrent Neural NetworksCode1
Physics-Informed Machine Learning of Dynamical Systems for Efficient Bayesian InferenceCode1
Physics-informed neural networks for highly compressible flowsCode1
Physics-informed Neural Networks-based Model Predictive Control for Multi-link ManipulatorsCode1
Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaicsCode1
Finite Operator Learning: Bridging Neural Operators and Numerical Methods for Efficient Parametric Solution and Optimization of PDEsCode1
Multi-Objective Loss Balancing for Physics-Informed Deep LearningCode1
STDEN: Towards Physics-Guided Neural Networks for Traffic Flow PredictionCode1
Physics-constrained deep learning postprocessing of temperature and humidityCode1
QCPINN: Quantum-Classical Physics-Informed Neural Networks for Solving PDEsCode1
Physics-informed machine learning techniques for edge plasma turbulence modelling in computational theory and experimentCode0
A Machine Learning Pressure Emulator for Hydrogen EmbrittlementCode0
Physics-informed Discretization-independent Deep Compositional Operator NetworkCode0
Physics-informed machine learning for the COVID-19 pandemic: Adherence to social distancing and short-term predictions for eight countriesCode0
Physics-Informed Machine Learning Method for Large-Scale Data Assimilation ProblemsCode0
Physics-informed kernel learningCode0
DSSRNN: Decomposition-Enhanced State-Space Recurrent Neural Network for Time-Series AnalysisCode0
Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin ModelsCode0
Physics-Informed Calibration of Aeromagnetic Compensation in Magnetic Navigation Systems using Liquid Time-Constant NetworksCode0
Physics-informed machine learning as a kernel methodCode0
Neural oscillators for generalization of physics-informed machine learningCode0
Differentiable Neural-Integrated Meshfree Method for Forward and Inverse Modeling of Finite Strain HyperelasticityCode0
Non-overlapping, Schwarz-type Domain Decomposition Method for Physics and Equality Constrained Artificial Neural NetworksCode0
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
PDE-DKL: PDE-constrained deep kernel learning in high dimensionalityCode0
A Physics-Augmented GraphGPS Framework for the Reconstruction of 3D Riemann Problems from Sparse DataCode0
Towards Size-Independent Generalization Bounds for Deep Operator NetsCode0
Differentiable Predictive Control for Large-Scale Urban Road NetworksCode0
An analysis of Universal Differential Equations for data-driven discovery of Ordinary Differential EquationsCode0
Noise-aware Physics-informed Machine Learning for Robust PDE DiscoveryCode0
Hyperspectral Blind Unmixing using a Double Deep Image PriorCode0
Kolmogorov n-Widths for Multitask Physics-Informed Machine Learning (PIML) Methods: Towards Robust MetricsCode0
Physics-Informed Deep Neural Networks for Transient Electromagnetic AnalysisCode0
A Statistical Evaluation of Indoor LoRaWAN Environment-Aware Propagation for 6G: MLR, ANOVA, and Residual Distribution AnalysisCode0
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