Change the repository type filter
All
Repositories list
183 repositories
ReservoirComputing.jl
PublicReservoir computing utilities for scientific machine learning (SciML)FindFirstFunctions.jl
PublicLinearSolve.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.SciMLBase.jl
PublicThe Base interface of the SciML ecosystem- The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
SimpleNonlinearSolve.jl
PublicFast and simple nonlinear solvers for the SciML common interface. Newton, Broyden, Bisection, Falsi, and more rootfinders on a standard interface.- CellMLToolkit.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- High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
SciMLBenchmarksOutput
PublicSciML-Bench Benchmarks for Scientific Machine Learning (SciML), Physics-Informed Machine Learning (PIML), and Scientific AI PerformanceNeuralLyapunov.jl
PublicSciMLStructures.jl
PublicBaseModelica.jl
Public- Symbolic-Numeric Universal Differential Equations for Automating Scientific Machine Learning (SciML)
ComponentArrays.jl
PublicArrays with arbitrarily nested named components.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 equations- A simple domain-specific language (DSL) for defining differential equations for use in scientific machine learning (SciML) and other applications
NonlinearSolve.jl
PublicHigh-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.SciMLDocs
PublicGlobal documentation for the Julia SciML Scientific Machine Learning OrganizationDataInterpolations.jl
PublicSciMLBenchmarks.jl
PublicScientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, RPSOGPU.jl
PublicCommonSolve.jl
PublicA common solve function for scientific machine learning (SciML) and beyondGlobalSensitivity.jl
PublicRobust, Fast, and Parallel Global Sensitivity Analysis (GSA) in JuliaDiffEqFlux.jl
PublicPre-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- Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem
- Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform Bayesian probabilistic scientific machine learning
OptimizationBase.jl
PublicSciMLBook
PublicParallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)