Oilman-programmer's repositories
iterative-ensemble-smoother
a simple demo on iterative ensemble smoother(ies) for inverse problem
PhyCRNet
Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
deep-learning-for-image-processing
deep learning for image processing including classification and object-detection etc.
NeuralSolvers
Neural network based solvers for partial differential equations and inverse problems :milky_way:. Implementation of physics-informed neural networks in pytorch.
Physics-Based-Deep-Learning
Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond
B-PINNs
Pytorch implementation of Bayesian physics-informed neural networks
sciann
Deep learning for Engineers - Physics Informed Deep Learning
Upscaling-based-on-TgCNN
Project: Efficient upscaling of geologic model based on theory-guided encoder-decoder
PINNs-TF2.0
TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).
PINN-1
Simple PyTorch Implementation of Physics Informed Neural Network (PINN)
TgNN-Surrogate
The construction of TgNN surrogate
PINNs
Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations
pinn_burgers
Physics Informed Neural Network (PINN) for Burgers' equation.