google-research / data-driven-advection
☆192Updated 3 years ago
Alternatives and similar repositories for data-driven-advection:
Users that are interested in data-driven-advection are comparing it to the libraries listed below
- Code for "Learning data-driven discretizations for partial differential equations"☆167Updated 5 years ago
- Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations☆279Updated 2 years ago
- High performance computational platform in Python for the spectral Galerkin method☆213Updated 4 months ago
- Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…☆147Updated 3 months ago
- Hidden physics models: Machine learning of nonlinear partial differential equations☆145Updated 5 years ago
- Spectral Navier Stokes (and similar) solvers in Python☆318Updated last year
- ☆116Updated 5 years ago
- Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers☆155Updated 2 years ago
- MeshfreeFlowNet: Physical Constrained Space Time Super-Resolution☆107Updated 4 years ago
- A list of papers relating Computational Physics and Machine Learning☆137Updated 6 years ago
- Immersed Boundary Projection Method☆110Updated 5 years ago
- PDE-Net: Learning PDEs from Data☆313Updated 3 years ago
- Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed c…☆114Updated 3 years ago
- Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond☆56Updated 4 years ago
- PyTorch-FEniCS interface☆100Updated 4 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆92Updated 2 years ago
- ☆250Updated 2 years ago
- PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks☆307Updated last year
- Hidden Fluid Mechanics☆321Updated 2 years ago
- Data-driven Reynolds stress modeling with physics-informed machine learning☆92Updated 6 years ago
- A library for dimensionality reduction on spatial-temporal PDE☆64Updated last year
- Solving PDEs with NNs☆53Updated 2 years ago
- Automatic Differentiation Library for Computational and Mathematical Engineering☆301Updated last year
- Differentiable Fluid Dynamics Package☆391Updated last week
- A flexible framework for solving PDEs with modern spectral methods.☆559Updated 3 weeks ago
- A code for fast, massively-parallel direct numerical simulations (DNS) of canonical flows☆223Updated this week
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆84Updated 4 years ago
- Simple one-dimensional examples of various hydrodynamics techniques☆114Updated 3 years ago
- A Python package for spectral proper orthogonal decomposition (SPOD).☆108Updated 4 months ago
- Turbulent flow network source code☆68Updated last month