132 Packages since 2013
User Packages
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ODE.jl106Assorted basic Ordinary Differential Equation solvers for scientific machine learning (SciML). Deprecated: Use DifferentialEquations.jl instead.
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Sundials.jl208Julia interface to Sundials, including a nonlinear solver (KINSOL), ODE's (CVODE and ARKODE), and DAE's (IDA) in a SciML scientific machine learning enabled manner
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DASSL.jl33Solves stiff differential algebraic equations (DAE) using variable stepsize backwards finite difference formula (BDF) in the SciML scientific machine learning organization
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DifferentialEquations.jl2841Multi-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.
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EllipsisNotation.jl88Julia-based implementation of ellipsis array indexing notation `..`
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ResettableStacks.jl7A stack implementation with a reset! function which avoids garbage collection for scientific machine learning (SciML)
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ParameterizedFunctions.jl77A simple domain-specific language (DSL) for defining differential equations for use in scientific machine learning (SciML) and other applications
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DiffEqFinancial.jl25Differential equation problem specifications and scientific machine learning for common financial models
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MultiScaleArrays.jl73A framework for developing multi-scale arrays for use in scientific machine learning (SciML) simulations
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DiffEqBase.jl309The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
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DiffEqDevTools.jl46Benchmarking, testing, and development tools for differential equations and scientific machine learning (SciML)
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StochasticDiffEq.jl248Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem
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OrdinaryDiffEq.jl533High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
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PyDSTool.jl7A wrapper for the Python PyDSTool library for the SciML Scientific Machine Learning organization
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DiffEqParamEstim.jl61Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions
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RecursiveArrayTools.jl212Tools for easily handling objects like arrays of arrays and deeper nestings in scientific machine learning (SciML) and other applications
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DiffEqProblemLibrary.jl55A library of premade problems for examples and testing differential equation solvers and other SciML scientific machine learning tools
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SciMLBenchmarks.jl318Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
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DiffEqTutorials.jl713Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
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SciMLTutorials.jl713Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
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DiffEqDocs.jl270Documentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem
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SciMLSensitivity.jl329A 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.
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DiffEqSensitivity.jl329A 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.
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SciMLExpectations.jl65Fast uncertainty quantification for scientific machine learning (SciML) and differential equations
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DiffEqUncertainty.jl65Fast uncertainty quantification for scientific machine learning (SciML) and differential equations
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DiffEqDevDocs.jl8Developer documentation for the SciML scientific machine learning ecosystem's differential equation solvers
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DASKR.jl12Interface to DASKR, a differential algebraic system solver for the SciML scientific machine learning ecosystem
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ODEInterfaceDiffEq.jl9Adds the common API onto ODEInterface classic Fortran methods for the SciML Scientific Machine Learning organization
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MATLABDiffEq.jl20Common interface bindings for the MATLAB ODE solvers via MATLAB.jl for the SciML Scientific Machine Learning ecosystem
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DiffEqPDEBase.jl5Library for common tools for solving PDEs with finite difference methods (FDM), finite volume methods (FVM), finite element methods (FEM), and psuedospectral methods in a way that integrates with the SciML Scientific Mechine Learning ecosystem
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DiffEqCallbacks.jl94A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers
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DelayDiffEq.jl59Delay differential equation (DDE) solvers in Julia for the SciML scientific machine learning ecosystem. Covers neutral and retarded delay differential equations, and differential-algebraic equations.
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DiffEqMonteCarlo.jl11Monte Carlo simulation routines for high-performance parallelization of differential equation solvers and scientific machine learning
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DiffEqJump.jl139Build 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)
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JumpProcesses.jl139Build 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)
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DiffEqBiological.jl455Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
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Catalyst.jl455Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
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NeuralPDE.jl966Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
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NeuralNetDiffEq.jl966Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
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BoundaryValueDiffEq.jl42Boundary value problem (BVP) solvers for scientific machine learning (SciML)
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