Sumant's repositories
PINN_TF2_NLS
Tensorflow 2 implementation of physics-informed neural network using Schrodinger simulation data (Raizzi et al. 2017)
18337
18.337 - Parallel Computing and Scientific Machine Learning
Deep-PDE-Solvers
Unbiased Deep Learning based Solvers for parametric PDEs
DeepBSDE
Deep BSDE solver in TensorFlow
deepxde
Deep learning library for solving differential equations
fourier_neural_operator
Use Fourier transform to learn operators in differential equations.
FreeFem-doc
FreeFEM user documentation
freefem-intro
Codes and materials for the "Introduction to finite element using FreeFEM" series.
HFM
Hidden Fluid Mechanics
hp-VPINNs
hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations
Latex-Tutorial
Introduction to LaTex for Beginners
moulin2019al
Augmented Lagrangian Preconditioner for Hydrodynamic Stability Analysis
nangs
Solving PDEs with NNs
neurodiffeq
A light-weight & flexible library for solving differential equations using neural networks based on PyTorch. Spatial-temporal ODEs and PDEs are both supported.
nnode
Neural network code for solving ordinary and partial differential equations
Physics-Based-Deep-Learning
Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond
PhysicsInformedPointNetPorousMedia
Prediction of Fluid Flow in Porous Media by Sparse Observations and Physics-Informed PointNet
PINN
Simple PyTorch Implementation of Physics Informed Neural Network (PINN)
PINNs
Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations
PINNs-Pytorch
PyTorch Implementation of Physics-informed Neural Networks
PINNs-TF2.0
TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).
pytorch-tutorials
Pytorch implementation for solving the differential equations
PyTorchTutorial
Examplary code for NN, MFNN, DynNet, PINNs and CNN
TL-PINNs
Boosting the training of physics informed neural networks with transfer learning
UQPINNs-TF2.0
TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks (UQPINNs).
XPINNs
Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonlinear Partial Differential Equations