SciML Open Source Scientific Machine Learning's repositories
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
NeuralPDE.jl
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
OrdinaryDiffEq.jl
High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
Catalyst.jl
Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
Surrogates.jl
Surrogate modeling and optimization for scientific machine learning (SciML)
SciMLBenchmarks.jl
Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
NonlinearSolve.jl
High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.
JumpProcesses.jl
Build and simulate jump equations like Gillespie simulations and jump diffusions with constant and state-dependent rates and mix with differential equations and scientific machine learning (SciML)
SciMLBase.jl
The Base interface of the SciML ecosystem
ParameterizedFunctions.jl
A simple domain-specific language (DSL) for defining differential equations for use in scientific machine learning (SciML) and other applications
DiffEqNoiseProcess.jl
A library of noise processes for stochastic systems like stochastic differential equations (SDEs) and other systems that are present in scientific machine learning (SciML)
SimpleNonlinearSolve.jl
Fast and simple nonlinear solvers for the SciML common interface. Newton, Broyden, Bisection, Falsi, and more rootfinders on a standard interface.
CellMLToolkit.jl
CellMLToolkit.jl is a Julia library that connects CellML models to the Scientific Julia ecosystem.
GlobalSensitivity.jl
Robust, Fast, and Parallel Global Sensitivity Analysis (GSA) in Julia
BoundaryValueDiffEq.jl
Boundary value problem (BVP) solvers for scientific machine learning (SciML)
SBMLToolkit.jl
SBML differential equation and chemical reaction model (Gillespie simulations) for Julia's SciML ModelingToolkit
ADTypes.jl
Repository for automatic differentiation backend types
ModelingToolkitCourse
A course on composable system modeling, differential-algebraic equations, acausal modeling, compilers for simulation, and building digital twins of real-world devices
ReactionNetworkImporters.jl
Julia Catalyst.jl importers for various reaction network file formats like BioNetGen and stoichiometry matrices
IRKGaussLegendre.jl
Implicit Runge-Kutta Gauss-Legendre 16th order (Julia)
FiniteStateProjection.jl
Finite State Projection algorithms for chemical reaction networks
ModelingToolkitNeuralNets.jl
Symbolic-Numeric Universal Differential Equations for Automating Scientific Machine Learning (SciML)
CommonSolve.jl
A common solve function for scientific machine learning (SciML) and beyond
SciMLBenchmarksOutput
SciML-Bench Benchmarks for Scientific Machine Learning (SciML), Physics-Informed Machine Learning (PIML), and Scientific AI Performance
OptimizationBase.jl
The base package for Optimization.jl, containing the structs and basic functions for it.
SciMLStructures.jl
A structure interface for SciML to give queryable properties from user data and parameters
SBMLToolkitTestSuite.jl
Functions to run the SBML Test Suite with SBMLToolkit, create logs and create reports for the SBML Test Suite Database
CatalystNetworkAnalysis.jl
Network analysis algorithms for reaction networks modeled using Catalyst.jl
BaseModelica.jl
Importers for the BaseModelica standard into the Julia ModelingToolkit ecosystem