XuhuiM / SciML-CourseLinks
☆45Updated 5 months ago
Alternatives and similar repositories for SciML-Course
Users that are interested in SciML-Course are comparing it to the libraries listed below
Sorting:
- A large-scale benchmark for machine learning methods in fluid dynamics☆236Updated 2 weeks ago
- ☆30Updated 10 months ago
- A solver for subsonic flow around airfoils based on physics-informed neural networks and mesh transformation☆31Updated last year
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆57Updated 3 years ago
- Modified Meshgraphnets with more features☆56Updated 9 months ago
- MIONet: Learning multiple-input operators via tensor product☆38Updated 2 years ago
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆86Updated last year
- ☆52Updated 10 months ago
- Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey☆236Updated 5 months ago
- Physics-informed neural networks for two-phase flow problems☆69Updated last month
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- A kind of loss function based on Least Squares Weighted Residual method for computational solid mechanics☆57Updated last year
- Implement PINN with high level APIs of TF2.0, including a solution of coupled PDEs with PINN☆27Updated 2 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆34Updated 3 years ago
- PDE Preserved Neural Network☆57Updated 5 months ago
- ☆41Updated 3 years ago
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆33Updated 3 years ago
- Official implementation of "PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network"☆52Updated 2 years ago
- Physics Informed Neural Networks: a starting step for CFD specialists☆38Updated 3 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆84Updated 2 months ago
- In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the Neur…☆56Updated 10 months ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆74Updated 2 years ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆26Updated 9 months ago
- ☆47Updated 3 years ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆51Updated 4 years ago
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆58Updated 4 years ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆98Updated 3 years ago
- A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks☆90Updated 3 years ago
- Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting☆37Updated 2 years ago
- parallel PINNs; RANS equations; spatiotemporal parallel; PINNs☆33Updated last year