Solver for two-dimensional conservation equations using the finite volume method in Julia.

Solvers for steady states in scientific machine learning (SciML)

Simpler stacktraces for the Julia Programming Language

A library of systems of partial differential equations, as defined with ModelingToolkit.jl in Julia

Julia Catalyst.jl importers for various reaction network file formats like BioNetGen and stoichiometry matrices

Differential equation problem specifications and scientific machine learning for common financial models

Stochastic delay differential equations (SDDE) solvers for the SciML scientific machine learning ecosystem

Implicit Runge-Kutta Gauss-Legendre 16th order (Julia)

Julia MathML parser

Simple differential equation solvers in native Julia for scientific machine learning (SciML)

Symbolic-Numeric Universal Differential Equations for Automating Scientific Machine Learning (SciML)

Wrappers for the SciPy differential equation solvers for the SciML Scientific Machine Learning organization

Common interface bindings for the MATLAB ODE solvers via MATLAB.jl for the SciML Scientific Machine Learning ecosystem

Under some conditions you may need this function

Finite State Projection algorithms for chemical reaction networks

A common solve function for scientific machine learning (SciML) and beyond

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Fast Poisson Random Numbers in pure Julia for scientific machine learning (SciML)

The base package for Optimization.jl, containing the structs and basic functions for it.

A general interface for symbolic indexing of SciML objects used in conjunction with Domain-Specific Languages

GPU accelerated Particle Swarm Optimization

High dimensional numbers and reductions recipes for data visualization of scientific machine learning (SciML)

Common types and interface for discretizers of ModelingToolkit PDESystems.

Interface to DASKR, a differential algebraic system solver for the SciML scientific machine learning ecosystem

Monte Carlo simulation routines for high-performance parallelization of differential equation solvers and scientific machine learning

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Differential equation solvers with global error estimation

Adds the common API onto ODEInterface classic Fortran methods for the SciML Scientific Machine Learning organization

Fixing the world one invalidator at a time.

A SciML symbolic-numeric compiler tool for investigating functions in order to perform optimizations

Wrappers for calling the R deSolve differential equation solvers from Julia for scientific machine learning (SciML)

Wrappers for GeometricIntegrators.jl into the SciML common interface for scientific machine learning (SciML)

Nonlinear solver bindings for the SciML Interface

Faster `findfirst(==(val), dense_vector)`.

Developer documentation for the SciML scientific machine learning ecosystem's differential equation solvers

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A structure interface for SciML to give queryable properties from user data and parameters

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A wrapper for the Python PyDSTool library for the SciML Scientific Machine Learning organization

A stack implementation with a reset! function which avoids garbage collection for scientific machine learning (SciML)