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/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
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/diffeqpy
Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization
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.
SciML/SciMLBenchmarks.jl
Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
SciML/NonlinearSolve.jl
High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.
SciML/SciMLBase.jl
The Base interface of the SciML ecosystem
SciML/ModelingToolkitStandardLibrary.jl
A standard library of components to model the world and beyond
SciML/PreallocationTools.jl
Tools for building non-allocating pre-cached functions in Julia, allowing for GC-free usage of automatic differentiation in complex codes
SciML/StructuralIdentifiability.jl
Fast and automatic structural identifiability software for ODE systems
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/ParameterizedFunctions.jl
A simple domain-specific language (DSL) for defining differential equations for use in scientific machine learning (SciML) and other applications
SciML/SciMLDocs
Global documentation for the Julia SciML Scientific Machine Learning Organization
SciML/CellMLToolkit.jl
CellMLToolkit.jl is a Julia library that connects CellML models to the Scientific Julia ecosystem.
SciML/DelayDiffEq.jl
Delay differential equation (DDE) solvers in Julia for the SciML scientific machine learning ecosystem. Covers neutral and retarded delay differential equations, and differential-algebraic equations.
SciML/DiffEqParamEstim.jl
Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions
SciML/GlobalSensitivity.jl
Robust, Fast, and Parallel Global Sensitivity Analysis (GSA) in Julia
SciML/MinimallyDisruptiveCurves.jl
Finds relationships between the parameters of a mathematical model
SciML/BoundaryValueDiffEq.jl
Boundary value problem (BVP) solvers for scientific machine learning (SciML)
SciML/CommonSolve.jl
A common solve function for scientific machine learning (SciML) and beyond
SciML/SciMLBenchmarksOutput
SciML-Bench Benchmarks for Scientific Machine Learning (SciML), Physics-Informed Machine Learning (PIML), and Scientific AI Performance
SciML/PoissonRandom.jl
Fast Poisson Random Numbers in pure Julia for scientific machine learning (SciML)
SciML/NeuralOperators.jl
DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia
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/SurrogatesBase.jl
Basically just a surrogate in disguise