physics-informed

There are 3 repositories under physics-informed topic.

mathLab / PINA
Physics-Informed Neural networks for Advanced modeling
physics-informed-neural-networks modeling machine-learning deep-learning python pytorch differential-equations ode pde physics-informed hacktoberfest lightining pinn equation-learning neural-networks neural-operators
Language:Python 267
pierremtb / PINNs-TF2.0
TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).
physics-informed deep-neural-networks tf2 partial-differential-equations mechanical-engineering
Language:Mathematica 237
cics-nd / ar-pde-cnn
Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs
bayesian-surrogate convolutional-neural-networks deep-learning partial-differential-equations physics-constrained physics-informed
Language:Python 82
JRice15 / physics-informed-autoencoders
Research project conducted at Pacific Northwest National Laboratory, exploring the use of physics-informed autoencoders to predict fluid flow dynamics
machine-learning physics-informed artificial-intelligence neural-network deep-learning
Language:Python 28
xiaoyuxie-vico / PyDimension
Dimensionless learning codes for our paper called "Data-driven discovery of dimensionless numbers and governing laws from scarce measurements".
deep-learning machine-learning manufacturing partial-differential-equations physics-informed scaling-laws scientific-machine-learning system-identification
Language:Jupyter Notebook 25
pierremtb / UQPINNs-TF2.0
TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks (UQPINNs).
physics-informed deep-neural-networks tf2 partial-differential-equations mechanical-engineering
Language:Python 16
SciML / SciMLBenchmarksOutput
SciML-Bench Benchmarks for Scientific Machine Learning (SciML), Physics-Informed Machine Learning (PIML), and Scientific AI Performance
differential-equations julia scientific-machine-learning sciml benchmarks gpu jax matlab neural-network performance physics-informed python pytorch r
Language:HTML 14
PredictiveScienceLab / pift-paper-2023
Physics-informed information field theory - Solve inverse problems with built-in model form uncertainty estimation
inverse-problems physics-informed uncertainty-quantification information-field-theory model-form-uncertainty
Language:C++ 10
JBris / physics_informed_neural_networks_tutorial
Going through the tutorial on Physics-informed Neural Networks: https://github.com/madagra/basic-pinn
physics-informed physics-informed-learning physics-informed-ml physics-informed-neural-network physics-informed-neural-networks physics-model pinns derivatives ode ode-model
Language:Jupyter Notebook 2
smrfeld / physics-based-ml-reaction-networks
Code for paper "Physics-based machine learning for modeling IP3 induced calcium oscillations" - DOI: 10.5281/zenodo.4839127
chemistry machine-learning physics-based physics-based-ml physics-informed physics-informed-ml reaction-networks reactions
Language:Mathematica 1
uq-group / uq-group.github.io
UQ Group (Director: Hadi Meidani)
uncertainty research machine-learning uncertainty-quantification computational-science stochastic physics-informed deep-learning deep-neural-networks smart-cities hadi-meidani pinns scientific-machine-learning illinois uiuc civil-engineering
Language:CSS 1