Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components
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
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
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)
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
Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem
Assorted basic Ordinary Differential Equation solvers for scientific machine learning (SciML)
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
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
Designs for new Base array interface primitives, used widely through scientific machine learning (SciML) and other organizations
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
Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions
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)
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)
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
Utility functions for exponential integrators 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