SOTAVerified

Physics-informed machine learning

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 176–192 of 192 papers

TitleStatusHype
Analyzing Koopman approaches to physics-informed machine learning for long-term sea-surface temperature forecastingCode1
QRnet: optimal regulator design with LQR-augmented neural networks—0
Physics-informed machine learning for the COVID-19 pandemic: Adherence to social distancing and short-term predictions for eight countriesCode0
Physics-Informed Deep Neural Networks for Transient Electromagnetic AnalysisCode0
Universal Battery Performance and Degradation Model for Electric Aircraft—0
Physics-informed machine learning for sensor fault detection with flight test data—0
Data-driven Optimal Power Flow: A Physics-Informed Machine Learning Approach—0
A physics-informed neural network for wind turbine main bearing fatigueCode1
Physics-informed machine learning for composition-process-property alloy design: shape memory alloy demonstration—0
Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaicsCode1
Learning ergodic averages in chaotic systems—0
Tensor Basis Gaussian Process Models of Hyperelastic Materials—0
Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systemsCode1
Physics-informed neural networks for corrosion-fatigue prognosisCode1
Physics-Informed Machine Learning Models for Predicting the Progress of Reactive-Mixing—0
Fleet Prognosis with Physics-informed Recurrent Neural NetworksCode1
Prediction of Reynolds Stresses in High-Mach-Number Turbulent Boundary Layers using Physics-Informed Machine Learning—0
Show:102550
← PrevPage 8 of 8Next →

No leaderboard results yet.