Search Packages

scikit-fem

Simple finite element assemblers

findiff

Python package for numerical derivatives and partial differential equations in any number of dimensions.

deepxde

A library for scientific machine learning and physics-informed learning

exponax

Efficient Differentiable n-d PDE Solvers in JAX.

pdequinox

Neural Emulator Architectures in JAX.

apebench

[Neurips 2024] A benchmark suite for autoregressive neural emulation of PDEs. (≥46 PDEs in 1D, 2D, 3D; Differentiable Physics; Unrolled Training; Rollout Metrics)

trainax

Neural Emulator Architectures in JAX.

devsim

TCAD Semiconductor Device Simulator

felupe

Finite Element Analysis

pina-mathlab

Physics-Informed Neural networks for Advanced modeling

phaethon

End-to-End Physics-Constrained Scientific Computing & Sci-ML Framework

sympde

Symbolic calculus for partial differential equations (and variational forms)

jaxdf

A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations

opinf

Operator Inference for data-driven model reduction of dynamical systems.

pinnrl

Physics-Informed Neural Networks with RL-based adaptive sampling for solving PDEs

layercake-model

LayerCake is a framework to design systems of partial differential equations (PDEs), and convert them to ordinary differential equations (ODEs) via Galerkin-type expansions.

rom-operator-inference

Operator inference for data-driven, non-intrusive model reduction of dynamical systems.

pyfrp

PyFRAP: A Python based FRAP analysis tool box

pyro-hydro

A python hydrodynamics code for teaching and prototyping

unitflex

End-to-End Physics-Constrained Scientific Computing & Sci-ML Framework

imscript

Image Processing with Unix Pipes

pyfvm

Finite volume discretization tools for Python.

kpca-deeponet

Nonlinear model reduction for operator learning

pysgpp

SG⁺⁺ – the numerical library for Sparse Grids in all their variants.