SciML Open Source Scientific Machine Learning
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180 repositories
SurrogatesBase.jl
Public- A general interface for symbolic indexing of SciML objects used in conjunction with Domain-Specific Languages
- The Base interface of the SciML ecosystem
OrdinaryDiffEq.jl
PublicHigh performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)- Lightweight and easy generation of quasi-Monte Carlo sequences with a ton of different methods on one API for easy parameter exploration in scientific machine learning (SciML)
ComponentArrays.jl
PublicArrays with arbitrarily nested named components.- Julia Catalyst.jl importers for various reaction network file formats like BioNetGen and stoichiometry matrices
- Boundary value problem (BVP) solvers for scientific machine learning (SciML)
- Fast and automatic structural identifiability software for ODE systems
PoissonRandom.jl
PublicFast Poisson Random Numbers in pure Julia for scientific machine learning (SciML)EllipsisNotation.jl
PublicGlobalSensitivity.jl
PublicRobust, Fast, and Parallel Global Sensitivity Analysis (GSA) in JuliaSciMLBenchmarksOutput
PublicSciML-Bench Benchmarks for Scientific Machine Learning (SciML), Physics-Informed Machine Learning (PIML), and Scientific AI Performance- Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
diffeqpy
PublicSolving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organizationCatalyst.jl
PublicChemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.FindFirstFunctions.jl
Public- CellMLToolkit.jl is a Julia library that connects CellML models to the Scientific Julia ecosystem.
NeuralOperators.jl
Public- Tools for building non-allocating pre-cached functions in Julia, allowing for GC-free usage of automatic differentiation in complex codes
DiffEqParamEstim.jl
PublicEasy scientific machine learning (SciML) parameter estimation with pre-built loss functions- Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
SciMLStructures.jl
PublicBaseModelica.jl
Public- A simple domain-specific language (DSL) for defining differential equations for use in scientific machine learning (SciML) and other applications
CommonSolve.jl
PublicA common solve function for scientific machine learning (SciML) and beyondModelingToolkit.jl
PublicAn 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- A standard library of components to model the world and beyond