Pinned Repositories
DiffEqFlux.jl
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
diffeqpy
Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization
diffeqr
Solving differential equations in R using DifferentialEquations.jl and the SciML Scientific Machine Learning ecosystem
DifferentialEquations.jl
Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.
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
Optimization.jl
Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.
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)
SciMLBook
Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)
SciMLTutorials.jl
Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
SciML Open Source Scientific Machine Learning's Repositories
SciML/SciMLBook
Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)
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/Optimization.jl
Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.
SciML/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)
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
SciML/StochasticDiffEq.jl
Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem
SciML/NonlinearSolve.jl
High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.
SciML/DataInterpolations.jl
A library of data interpolation and smoothing functions
SciML/Sundials.jl
Julia interface to Sundials, including a nonlinear solver (KINSOL), ODEs (CVODE and ARKODE), and DAEs (IDA)
SciML/SciMLBase.jl
The Base interface of the SciML ecosystem
SciML/QuasiMonteCarlo.jl
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)
SciML/RuntimeGeneratedFunctions.jl
Functions generated at runtime without world-age issues or overhead
SciML/EllipsisNotation.jl
Julia-based implementation of ellipsis array indexing notation `..`
SciML/SciMLDocs
Global documentation for the Julia SciML Scientific Machine Learning Organization
SciML/ParameterizedFunctions.jl
A simple domain-specific language (DSL) for defining differential equations for use in scientific machine learning (SciML) and other applications
SciML/CellMLToolkit.jl
CellMLToolkit.jl is a Julia library that connects CellML models to the Scientific Julia ecosystem.
SciML/sciml.ai
The SciML Scientific Machine Learning Software Organization Website
SciML/ADTypes.jl
Repository for automatic differentiation backend types
SciML/SciMLOperators.jl
SciMLOperators.jl: Matrix-Free Operators for the SciML Scientific Machine Learning Common Interface in Julia
SciML/BoundaryValueDiffEq.jl
Boundary value problem (BVP) solvers for scientific machine learning (SciML)
SciML/SciMLBenchmarksOutput
SciML-Bench Benchmarks for Scientific Machine Learning (SciML), Physics-Informed Machine Learning (PIML), and Scientific AI Performance
SciML/DataInterpolationsND.jl
Interpolation of arbitrarily high dimensional array data
SciML/PoissonRandom.jl
Fast Poisson Random Numbers in pure Julia for scientific machine learning (SciML)
SciML/FindFirstFunctions.jl
Faster `findfirst(==(val), dense_vector)`.
SciML/SciMLStructures.jl
A structure interface for SciML to give queryable properties from user data and parameters
SciML/BaseModelica.jl
Importers for the BaseModelica standard into the Julia ModelingToolkit ecosystem
SciML/SBMLToolkitTestSuite.jl
Functions to run the SBML Test Suite with SBMLToolkit, create logs and create reports for the SBML Test Suite Database
SciML/NeuralLyapunov.jl
A library for searching for neural Lyapunov functions in Julia.
SciML/OrdinaryDiffEqOperatorSplitting.jl
Toolbox to handle and solve split formulations of a wide variety of ODE and DAE problems.