raj-brown / APMA_2070_ENGN_2912_SPRING_2024
☆51Updated 3 months ago
Alternatives and similar repositories for APMA_2070_ENGN_2912_SPRING_2024:
Users that are interested in APMA_2070_ENGN_2912_SPRING_2024 are comparing it to the libraries listed below
- ☆52Updated 2 years ago
- ☆45Updated last year
- Sparse Physics-based and Interpretable Neural Networks☆47Updated 3 years ago
- Basic implementation of physics-informed neural network with pytorch.☆57Updated 2 years ago
- Original implementation of fast PINN optimization with RBA weights☆47Updated 4 months ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆31Updated 7 months ago
- Non-adaptive and residual-based adaptive sampling for PINNs☆65Updated 2 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆49Updated 3 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆63Updated 2 years ago
- ☆103Updated 2 weeks ago
- MIONet: Learning multiple-input operators via tensor product☆31Updated 2 years ago
- POD-PINN code and manuscript☆47Updated 3 months ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆84Updated last year
- PINNs for 2D Incompressible Navier-Stokes Equation☆39Updated 9 months ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆82Updated 4 years ago
- Multi-fidelity reduced-order surrogate modeling☆19Updated 2 months ago
- XPINN code written in TensorFlow 2☆27Updated 2 years ago
- PDE Preserved Neural Network☆45Updated 7 months ago
- Here I will try to implement the solution of PDEs using PINN on pytorch for educational purpose☆44Updated 2 years ago
- DeepONet extrapolation☆25Updated last year
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆62Updated 3 years ago
- Physics-informed neural networks for two-phase flow problems☆51Updated 2 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆75Updated 2 years ago
- Burgers equation solved by PINN in PyTorch☆20Updated 3 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆22Updated 10 months ago
- ☆42Updated 2 months ago
- Code for 'Physics-Informed Neural Networks for Shell Structures'☆34Updated 6 months ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆67Updated last year
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆63Updated 2 years ago
- This repository is the official project page of the course AI in the Sciences and Engineering, ETH Zurich.☆165Updated 2 months ago