physics-informed
There are 13 repositories under physics-informed topic.
mathLab/PINA
Physics-Informed Neural networks for Advanced modeling
pierremtb/PINNs-TF2.0
TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).
cics-nd/ar-pde-cnn
Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs
xiaoyuxie-vico/PyDimension
Dimensionless learning codes for our paper called "Data-driven discovery of dimensionless numbers and governing laws from scarce measurements".
JRice15/physics-informed-autoencoders
Research project conducted at Pacific Northwest National Laboratory, exploring the use of physics-informed autoencoders to predict fluid flow dynamics
SciML/SciMLBenchmarksOutput
SciML-Bench Benchmarks for Scientific Machine Learning (SciML), Physics-Informed Machine Learning (PIML), and Scientific AI Performance
pierremtb/UQPINNs-TF2.0
TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks (UQPINNs).
PredictiveScienceLab/pift-paper-2023
Physics-informed information field theory - Solve inverse problems with built-in model form uncertainty estimation
JBris/physics_informed_neural_networks_tutorial
Going through the tutorial on Physics-informed Neural Networks: https://github.com/madagra/basic-pinn
smrfeld/physics-based-ml-reaction-networks
Code for paper "Physics-based machine learning for modeling IP3 induced calcium oscillations" - DOI: 10.5281/zenodo.4839127
uq-group/uq-group.github.io
UQ Group (Director: Hadi Meidani)
CheolJ/PINN-trend
Short review of Physics-Informed ML/DL
mohsensadr/DiscoverPDEAdjoint
Data-driven discovery of PDEs using the Adjoint method