SOTAVerified

Physics-informed machine learning

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–25 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
Social Physics Informed Diffusion Model for Crowd SimulationCode1
Physics-informed neural networks for corrosion-fatigue prognosisCode1
STDEN: Towards Physics-Guided Neural Networks for Traffic Flow PredictionCode1
Physics-Informed Machine Learning Simulator for Wildfire PropagationCode1
Physics-Informed Machine Learning of Dynamical Systems for Efficient Bayesian InferenceCode1
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
Physics-informed neural networks for highly compressible flowsCode1
QCPINN: Quantum-Classical Physics-Informed Neural Networks for Solving PDEsCode1
Physics-informed machine learning with differentiable programming for heterogeneous underground reservoir pressure managementCode1
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
Physics-constrained deep learning postprocessing of temperature and humidityCode1
Multi-Objective Loss Balancing for Physics-Informed Deep LearningCode1
Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaicsCode1
Physics informed machine learning with Smoothed Particle Hydrodynamics: Hierarchy of reduced Lagrangian models of turbulenceCode1
Physics-informed Neural Networks-based Model Predictive Control for Multi-link ManipulatorsCode1
Fleet Prognosis with Physics-informed Recurrent Neural NetworksCode1
LaPON: A Lagrange's-mean-value-theorem-inspired operator network for solving PDEs and its application on NSECode0
Show:102550
← PrevPage 1 of 8Next →

No leaderboard results yet.