oscar-rincon / ReScience-PINNsLinks
Replication with PyTorch of ''Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations'' by M. Raissi, P. Perdikaris, and G.E. Karniadakis from 2019.
☆27Updated last year
Alternatives and similar repositories for ReScience-PINNs
Users that are interested in ReScience-PINNs are comparing it to the libraries listed below
Sorting:
- Physics-Informed Neural Network (PINN) for Solving Direct and Inverse Heat Conduction Problems☆13Updated 3 years ago
- Physics-guided neural network framework for elastic plates☆45Updated 3 years ago
- A kind of loss function based on Least Squares Weighted Residual method for computational solid mechanics☆56Updated last year
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆27Updated 2 years ago
- Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting☆37Updated 2 years ago
- An unsupervised latent/output physics-informed convolutional-LSTM network for solving partial differential equations using peridynamic di…☆29Updated 2 years ago
- Physics-Informed Neural Network☆87Updated last year
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆95Updated 3 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆32Updated 3 years ago
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆56Updated 4 years ago
- POD-PINN code and manuscript☆52Updated 8 months ago
- Physics-informed radial basis network☆31Updated last year
- PINN program for computational mechanics☆116Updated last year
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆78Updated last year
- Pytorch implementation of Bayesian physics-informed neural networks☆60Updated 3 years ago
- A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks☆85Updated 2 years ago
- Physics-Informed Neural Network, Finite Element Method enhanced neural network, and FEM data-based neural network☆18Updated 5 months ago
- Implementation of 'Physics-Informed Neural Networks for Shell Structures' (European Journal of Mechanics A)☆39Updated 11 months ago
- ☆19Updated last year
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆56Updated 3 years ago
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆72Updated 3 years ago
- This is the code of my master thesis.☆140Updated 3 months ago
- Implementation of Physics-Informed Neural Networks for Computational Mechanics based on the DeepXDE package.☆40Updated last week
- Physics Informed Neural Network (PINN) for Burgers' equation.☆71Updated 11 months ago
- A-PINN: Auxiliary physics informed neural networks for forward and inverse problems of nonlinear integro-differential equations☆20Updated 2 years ago
- PINNs for 2D Incompressible Navier-Stokes Equation☆51Updated last year
- Implement PINN with high level APIs of TF2.0, including a solution of coupled PDEs with PINN☆27Updated 2 years ago
- PINN in solving Navier–Stokes equation☆107Updated 5 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- Competitive Physics Informed Networks☆31Updated 10 months ago