SciML Open Source Scientific Machine Learning
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JumpProcesses.jl
PublicBuild 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)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)- A general interface for symbolic indexing of SciML objects used in conjunction with Domain-Specific Languages
ModelingToolkit.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 equationsCatalyst.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.SciMLBase.jl
PublicThe Base interface of the SciML ecosystemBoundaryValueDiffEq.jl
PublicBoundary value problem (BVP) solvers for scientific machine learning (SciML)- 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.
SciMLSensitivity.jl
PublicA component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.- A simple domain-specific language (DSL) for defining differential equations for use in scientific machine learning (SciML) and other applications
DiffEqBase.jl
PublicThe lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problemsCellMLToolkit.jl
PublicCellMLToolkit.jl is a Julia library that connects CellML models to the Scientific Julia ecosystem.- Fast and automatic structural identifiability software for ODE systems
- Symbolic-Numeric Neural DAEs and Universal Differential Equations for Automating Scientific Machine Learning (SciML)
- A common solve function for scientific machine learning (SciML) and beyond
Optimization.jl
PublicMathematical 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.IRKGaussLegendre.jl
PublicNonlinearSolve.jl
PublicHigh-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.FiniteVolumeMethod1D.jl
PublicImplementation of the finite volume method in 1D.ExponentialUtilities.jl
PublicFast and differentiable implementations of matrix exponentials, Krylov exponential matrix-vector multiplications ("expmv"), KIOPS, ExpoKit functions, and more. All your exponential needs in SciML form.CurveFit.jl
Public- Implicit Layer Machine Learning via Deep Equilibrium Networks, O(1) backpropagation with accelerated convergence.
- Reservoir computing utilities for scientific machine learning (SciML)
- SymbolicNumericIntegration.jl: Symbolic-Numerics for Solving Integrals
ComponentArrays.jl
PublicArrays with arbitrarily nested named components.- Stochastic delay differential equations (SDDE) solvers for the SciML scientific machine learning ecosystem
SciMLWorkshop.jl
PublicWorkshop materials for training in scientific computing and scientific machine learning