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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 1–50 of 192 papers

TitleStatusHype
NeuralFoil: An Airfoil Aerodynamics Analysis Tool Using Physics-Informed Machine LearningCode3
Non-destructive Degradation Pattern Decoupling for Ultra-early Battery Prototype Verification Using Physics-informed Machine LearningCode2
Physics-Informed Machine Learning: A Survey on Problems, Methods and ApplicationsCode2
Fully-fused Multi-Layer Perceptrons on Intel Data Center GPUsCode2
Adaptive Training of Grid-Dependent Physics-Informed Kolmogorov-Arnold NetworksCode2
A physics-informed neural network for wind turbine main bearing fatigueCode1
Multi-Objective Loss Balancing for Physics-Informed Deep LearningCode1
Physics-constrained deep learning postprocessing of temperature and humidityCode1
Physics-informed neural networks for highly compressible flowsCode1
STDEN: Towards Physics-Guided Neural Networks for Traffic Flow PredictionCode1
Physics-informed Neural Networks-based Model Predictive Control for Multi-link ManipulatorsCode1
Physics informed machine learning with Smoothed Particle Hydrodynamics: Hierarchy of reduced Lagrangian models of turbulenceCode1
Analyzing Koopman approaches to physics-informed machine learning for long-term sea-surface temperature forecastingCode1
Finite Operator Learning: Bridging Neural Operators and Numerical Methods for Efficient Parametric Solution and Optimization of PDEsCode1
Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systemsCode1
A Gaussian Process Framework for Solving Forward and Inverse Problems Involving Nonlinear Partial Differential EquationsCode1
Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaicsCode1
Physics-Informed Machine Learning of Dynamical Systems for Efficient Bayesian InferenceCode1
Physics-informed neural networks for corrosion-fatigue prognosisCode1
Social Physics Informed Diffusion Model for Crowd SimulationCode1
Fleet Prognosis with Physics-informed Recurrent Neural NetworksCode1
QCPINN: Quantum-Classical Physics-Informed Neural Networks for Solving PDEsCode1
Physics-Informed Machine Learning Simulator for Wildfire PropagationCode1
Physics-informed machine learning with differentiable programming for heterogeneous underground reservoir pressure managementCode1
A Mechanism-Learning Deeply Coupled Model for Remote Sensing Retrieval of Global Land Surface Temperature—0
A physics-informed machine learning model for reconstruction of dynamic loads—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
A Physics-informed machine learning model for time-dependent wave runup prediction—0
TS-PIELM: Time-Stepping Physics-Informed Extreme Learning Machine Facilitates Soil Consolidation Analyses—0
A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems—0
A Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study—0
AI Foundation Models for Weather and Climate: Applications, Design, and Implementation—0
A Physics-informed Machine Learning-based Control Method for Nonlinear Dynamic Systems with Highly Noisy Measurements—0
Discrete-Time Nonlinear Feedback Linearization via Physics-Informed Machine Learning—0
Advancing Hybrid Quantum Neural Network for Alternative Current Optimal Power Flow—0
A comprehensive and FAIR comparison between MLP and KAN representations for differential equations and operator networks—0
FMEnets: Flow, Material, and Energy networks for non-ideal plug flow reactor design—0
A Physics-Informed Machine Learning Approach for Solving Heat Transfer Equation in Advanced Manufacturing and Engineering Applications—0
Physics-informed machine learning for composition-process-property alloy design: shape memory alloy demonstration—0
Neural Operator: Is data all you need to model the world? An insight into the impact of Physics Informed Machine Learning—0
Feature-adjacent multi-fidelity physics-informed machine learning for partial differential equations—0
DeepONet for Solving Nonlinear Partial Differential Equations with Physics-Informed Training—0
AdjointNet: Constraining machine learning models with physics-based codes—0
Discovering Artificial Viscosity Models for Discontinuous Galerkin Approximation of Conservation Laws using Physics-Informed Machine Learning—0
Discovering nonlinear resonances through physics-informed machine learning—0
A Data-driven Crowd Simulation Framework Integrating Physics-informed Machine Learning with Navigation Potential Fields—0
A Physics-Informed Machine Learning Approach for Solving Distributed Order Fractional Differential Equations—0
Efficient Bayesian Physics Informed Neural Networks for Inverse Problems via Ensemble Kalman Inversion—0
A Comparative Evaluation of Additive Separability Tests for Physics-Informed Machine Learning—0
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