SciML Open Source Scientific Machine Learning
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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)DataInterpolations.jl
Public- Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
- Julia Catalyst.jl importers for various reaction network file formats like BioNetGen and stoichiometry matrices
- Fast and automatic structural identifiability software for ODE systems
- Surrogate modeling and optimization for scientific machine learning (SciML)
sciml.ai
PublicThe SciML Scientific Machine Learning Software Organization Website- Fast Poisson Random Numbers in pure Julia for scientific machine learning (SciML)
NeuralPDE.jl
PublicPhysics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulationEllipsisNotation.jl
PublicMethodOfLines.jl
PublicAutomatic Finite Difference PDE solving with Julia SciMLGlobalSensitivity.jl
PublicRobust, Fast, and Parallel Global Sensitivity Analysis (GSA) in JuliaNeuralLyapunov.jl
PublicSciMLDocs
PublicGlobal documentation for the Julia SciML Scientific Machine Learning Organization- Reservoir computing utilities for scientific machine learning (SciML)
FindFirstFunctions.jl
PublicSciMLBase.jl
PublicThe Base interface of the SciML ecosystemCellMLToolkit.jl
PublicCellMLToolkit.jl is a Julia library that connects CellML models to the Scientific Julia ecosystem.PreallocationTools.jl
PublicTools for building non-allocating pre-cached functions in Julia, allowing for GC-free usage of automatic differentiation in complex codes- A standard library of components to model the world and beyond
- A simple domain-specific language (DSL) for defining differential equations for use in scientific machine learning (SciML) and other applications
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.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.ADTypes.jl
Public- Symbolic-Numeric Universal Differential Equations for Automating Scientific Machine Learning (SciML)
CommonSolve.jl
PublicA common solve function for scientific machine learning (SciML) and beyondNonlinearSolve.jl
PublicHigh-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.