SciML Open Source Scientific Machine Learning
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SciMLDocs
PublicGlobal documentation for the Julia SciML Scientific Machine Learning OrganizationDataInterpolations.jl
Public- Tools for building non-allocating pre-cached functions in Julia, allowing for GC-free usage of automatic differentiation in complex codes
- Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
SciMLBenchmarks.jl
PublicScientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, RSciMLStructures.jl
PublicBaseModelica.jl
PublicDiffEqBase.jl
PublicThe lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems- A simple domain-specific language (DSL) for defining differential equations for use in scientific machine learning (SciML) and other applications
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.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)ReservoirComputing.jl
PublicReservoir computing utilities for scientific machine learning (SciML)CommonSolve.jl
PublicA common solve function for scientific machine learning (SciML) and beyondBoundaryValueDiffEq.jl
PublicBoundary value problem (BVP) solvers for scientific machine learning (SciML)DifferentialEquations.jl
PublicMulti-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.DiffEqGPU.jl
PublicGPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem- Implicit Layer Machine Learning via Deep Equilibrium Networks, O(1) backpropagation with accelerated convergence.
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.LinearSolve.jl
PublicLinearSolve.jl: High-Performance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, add preconditioners, and all in one interface.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 equationsSurrogates.jl
PublicSurrogate modeling and optimization for scientific machine learning (SciML)Integrals.jl
PublicA common interface for quadrature and numerical integration for the SciML scientific machine learning organizationRecursiveArrayTools.jl
PublicSurrogatesBase.jl
PublicNeuralPDE.jl
PublicPhysics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation- Fast and automatic structural identifiability software for ODE systems
NonlinearSolve.jl
PublicHigh-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.SciMLBook
PublicParallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)QuasiMonteCarlo.jl
PublicLightweight 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)