aid4nscud / PINNResearchLinks
Physics-Informed Neural Networks: Forward/Inverse Modeling of Partial Differential Equations
☆17Updated last year
Alternatives and similar repositories for PINNResearch
Users that are interested in PINNResearch are comparing it to the libraries listed below
Sorting:
- ☆24Updated last year
- ☆14Updated last year
- Physics-informed neural network for fatigue crack propagation (Paris' law)☆18Updated 3 years ago
- Code of the publication "Physics informed neural networks for continuum micromechanics" published in https://doi.org/10.1016/j.cma.2022.1…☆18Updated 3 years ago
- Burgers equation solved by PINN in PyTorch☆24Updated 4 years ago
- Neural integration for constitutive equations☆11Updated last year
- Deep finite volume method☆22Updated last year
- Implementation of Physics-Informed Neural Networks for Computational Mechanics based on the DeepXDE package.☆45Updated this week
- This project is divided in a two parts. In first study, Lame parameters are identified using tanh activation function. After that, six a…☆13Updated 2 years ago
- Physics-informed deep learning for structural dynamics under moving load☆16Updated last year
- Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms☆12Updated 11 months ago
- An unsupervised latent/output physics-informed convolutional-LSTM network for solving partial differential equations using peridynamic di…☆31Updated 3 years ago
- PINNs for 2D Incompressible Navier-Stokes Equation☆53Updated last year
- Data preprocess method on Physics-informed neural networks☆22Updated 8 months ago
- A Julia module for stochastic response analysis by DR-PDEE/GE-GDEE☆11Updated 2 years ago
- CCSNet: a deep learning modeling suite for CO2 storage☆25Updated last year
- Physics Informed Neural Network (PINN) for Burgers' equation.☆71Updated last year
- ☆13Updated 4 years ago
- ☆39Updated last year
- ☆73Updated last year
- Density-based topology optimization via the deep energy method☆15Updated 2 years ago
- Prediction and control of fracture paths in disordered architected materials using graph neural networks☆12Updated 2 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆30Updated 3 years ago
- Implementation of a new hybrid machine learning technique for multi-fidelity surrogates of finite elements models with applications in mu…☆13Updated last year
- Implement PINN with high level APIs of TF2.0, including a solution of coupled PDEs with PINN☆27Updated 2 years ago
- Implementations of the "randomize-then-optimize" approach for sampling Bayesian Physics-informed Neural Network posteriors☆11Updated 6 months ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆51Updated 4 years ago
- ☆22Updated last year
- ☆25Updated last year
- ☆16Updated last year