Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components

A 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

Universal neural differential equations with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

High performance differential equation solvers for ordinary differential equations, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)

Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software

Linear operators for discretizations of differential equations and scientific machine learning (SciML)

Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem

Julia 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

The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems

Assorted basic Ordinary Differential Equation solvers for scientific machine learning (SciML)

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

Tools for easily handling objects like arrays of arrays and deeper nestings in scientific machine learning (SciML) and other applications

A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, and more for ODEs, SDEs, DDEs, DAEs, etc.

A differentiable simulator for scientific machine learning (SciML) with N-body problems, including astrophysical and molecular dynamics

Arrays which also have a label for each element for easy scientific machine learning (SciML)

A simple domain-specific language (DSL) for defining differential equations for use in scientific machine learning (SciML) and other applications

A scientific machine learning (SciML) wrapper for the FEniCS Finite Element library in the Julia programming language

A framework for developing multi-scale arrays for use in scientific machine learning (SciML) simulations

A library for building differential equations arising from physical problems for physics-informed and scientific machine learning (SciML)

Uncertainty quantification for scientific machine learning (SciML) and differential equations

Build 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)

Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions

A library of noise processes for stochastic systems like stochastic differential equations (SDEs) and other systems that are present in scientific machine learning (SciML)

Benchmarking, testing, and development tools for differential equations and scientific machine learning (SciML)

Utility functions for exponential integrators for the SciML scientific machine learning ecosystem

A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers

Solves stiff differential algebraic equations (DAE) using variable stepsize backwards finite difference formula (BDF) in the SciML scientific machine learning organization

Delay differential equation solvers for the SciML scientific machine learning ecosystem

A library of premade problems for examples and testing differential equation solvers and other SciML scientific machine learning tools

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