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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
Adaptive Training of Grid-Dependent Physics-Informed Kolmogorov-Arnold NetworksCode2
Non-destructive Degradation Pattern Decoupling for Ultra-early Battery Prototype Verification Using Physics-informed Machine LearningCode2
Fully-fused Multi-Layer Perceptrons on Intel Data Center GPUsCode2
Physics-Informed Machine Learning: A Survey on Problems, Methods and ApplicationsCode2
QCPINN: Quantum-Classical Physics-Informed Neural Networks for Solving PDEsCode1
Finite Operator Learning: Bridging Neural Operators and Numerical Methods for Efficient Parametric Solution and Optimization of PDEsCode1
Social Physics Informed Diffusion Model for Crowd SimulationCode1
A Gaussian Process Framework for Solving Forward and Inverse Problems Involving Nonlinear Partial Differential EquationsCode1
Physics-informed neural networks for highly compressible flowsCode1
Physics-constrained deep learning postprocessing of temperature and humidityCode1
Physics-Informed Machine Learning of Dynamical Systems for Efficient Bayesian InferenceCode1
STDEN: Towards Physics-Guided Neural Networks for Traffic Flow PredictionCode1
Physics-informed machine learning with differentiable programming for heterogeneous underground reservoir pressure managementCode1
Physics informed machine learning with Smoothed Particle Hydrodynamics: Hierarchy of reduced Lagrangian models of turbulenceCode1
Multi-Objective Loss Balancing for Physics-Informed Deep LearningCode1
Physics-informed Neural Networks-based Model Predictive Control for Multi-link ManipulatorsCode1
Physics-Informed Machine Learning Simulator for Wildfire PropagationCode1
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
Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaicsCode1
Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systemsCode1
Physics-informed neural networks for corrosion-fatigue prognosisCode1
Fleet Prognosis with Physics-informed Recurrent Neural NetworksCode1
Physics-Informed Machine Learning Regulated by Finite Element Analysis for Simulation Acceleration of Laser Powder Bed Fusion—0
TS-PIELM: Time-Stepping Physics-Informed Extreme Learning Machine Facilitates Soil Consolidation Analyses—0
Solving engineering eigenvalue problems with neural networks using the Rayleigh quotient—0
BridgeNet: A Hybrid, Physics-Informed Machine Learning Framework for Solving High-Dimensional Fokker-Planck Equations—0
Toward Knowledge-Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human-AI Synergy—0
A Physics-Augmented GraphGPS Framework for the Reconstruction of 3D Riemann Problems from Sparse DataCode0
Toward Physics-Informed Machine Learning for Data Center Operations: A Tropical Case Study—0
Scientific machine learning in Hydrology: a unified perspective—0
Fourier-Invertible Neural Encoder (FINE) for Homogeneous Flows—0
Reconstructing Physics-Informed Machine Learning for Traffic Flow Modeling: a Multi-Gradient Descent and Pareto Learning ApproachCode0
LaPON: A Lagrange's-mean-value-theorem-inspired operator network for solving PDEs and its application on NSECode0
Beyond Accuracy: EcoL2 Metric for Sustainable Neural PDE Solvers—0
Potential failures of physics-informed machine learning in traffic flow modeling: theoretical and experimental analysis—0
FMEnets: Flow, Material, and Energy networks for non-ideal plug flow reactor design—0
A Statistical Evaluation of Indoor LoRaWAN Environment-Aware Propagation for 6G: MLR, ANOVA, and Residual Distribution AnalysisCode0
Breaking the Diffraction Barrier for Passive Sources: Parameter-Decoupled Superresolution Assisted by Physics-Informed Machine Learning—0
Safe Physics-Informed Machine Learning for Dynamics and Control—0
A Mechanism-Learning Deeply Coupled Model for Remote Sensing Retrieval of Global Land Surface Temperature—0
Physics-informed Modularized Neural Network for Advanced Building Control by Deep Reinforcement Learning—0
Transforming Future Data Center Operations and Management via Physical AI—0
Physics-informed machine learning for building performance simulation-A review of a nascent field—0
Physics-Informed Deep B-Spline Networks for Dynamical Systems—0
Further Exploration of Precise Binding Energies from Physics Informed Machine Learning and the Development of a Practical Ensemble Model—0
A Multimodal Physics-Informed Neural Network Approach for Mean Radiant Temperature Modeling—0
A physics-informed Bayesian optimization method for rapid development of electrical machines—0
An interpretation of the Brownian bridge as a physics-informed prior for the Poisson equation—0
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