pde
There are 355 repositories under pde topic.
processing/processing
Source code for the Processing Core and Development Environment (PDE)
lululxvi/deepxde
A library for scientific machine learning and physics-informed learning
neuraloperator/neuraloperator
Learning in infinite dimension with neural operators.
SciML/ModelingToolkit.jl
An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
SciML/NeuralPDE.jl
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
SciML/SciMLTutorials.jl
Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
kinnala/scikit-fem
Simple finite element assemblers
maroba/findiff
Python package for numerical derivatives and partial differential equations in any number of dimensions.
Calsign/APDE
Source code for APDE: Create and run Processing sketches on an Android device.
precise-simulation/featool-multiphysics
FEATool - "Physics Simulation Made Easy" (Fully Integrated FEA, FEniCS, OpenFOAM, SU2 Solver GUI & Multi-Physics Simulation Platform)
SciML/DiffEqBase.jl
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
SciML/SciMLBenchmarks.jl
Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
python-hydro/pyro2
A framework for hydrodynamics explorations and prototyping
AMReX-Astro/Castro
Castro (Compressible Astrophysics): An adaptive mesh, astrophysical compressible (radiation-, magneto-) hydrodynamics simulation code for massively parallel CPU and GPU architectures.
bifurcationkit/BifurcationKit.jl
A Julia package to perform Bifurcation Analysis
SciML/DiffEqOperators.jl
Linear operators for discretizations of differential equations and scientific machine learning (SciML)
mathLab/PINA
Physics-Informed Neural networks for Advanced modeling
Alexis12119/nvim-config
Generalized and Personalized
SciML/NeuralOperators.jl
DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia
boutproject/BOUT-dev
BOUT++: Plasma fluid finite-difference simulation code in curvilinear coordinate systems
devsim/devsim
TCAD Semiconductor Device Simulator
megalithic/dotfiles
🗿 dotfilery, configuration, environment settings, automation, etc. 🛖
clawpack/pyclaw
PyClaw is a Python-based interface to the algorithms of Clawpack and SharpClaw. It also contains the PetClaw package, which adds parallelism through PETSc.
SciML/MethodOfLines.jl
Automatic Finite Difference PDE solving with Julia SciML
processing-r/Processing.R
R Language Mode in Processing for Creative Coding, created by @gaocegege, maintained by @jeremydouglass
vavrines/Kinetic.jl
Universal modeling and simulation of fluid mechanics upon machine learning. From the Boltzmann equation, heading towards multiscale and multiphysics flows.
matthieugomez/EconPDEs.jl
Solve non-linear HJB equations.
mnhrdt/imscript
a collection of small and standalone utilities for image processing, written in C
eth-vaw-glaciology/course-101-0250-00
ETH course - Solving PDEs in parallel on GPUs
nosvagor/dotfiles
🍙 my Personalized Development Environment [PDE]
python-hydro/hydro_examples
Simple one-dimensional examples of various hydrodynamics techniques
ucl-bug/jaxdf
A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations
camlab-ethz/ConvolutionalNeuralOperator
This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs
SciML/FEniCS.jl
A scientific machine learning (SciML) wrapper for the FEniCS Finite Element library in the Julia programming language
danielnehrig/nvim
neovim lua cfg
kaist-silab/awesome-graph-pde
Collection of resources about partial differential equations, graph neural networks, deep learning and dynamical system simulation