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21 search results found

Modelingtoolkit.jl ⭐ 1,292

An 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

Neuralpde.jl ⭐ 864

Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

Diffeqflux.jl ⭐ 810

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

Scimltutorials.jl ⭐ 698

Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.

Ordinarydiffeq.jl ⭐ 479

High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)

Diffeqpy ⭐ 456

Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization

Diffeqbase.jl ⭐ 282

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

Sundials.jl ⭐ 200

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

Diffeqr ⭐ 127

Solving differential equations in R using DifferentialEquations.jl and the SciML Scientific Machine Learning ecosystem

Diffeqbayes.jl ⭐ 119

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

Scimlbase.jl ⭐ 111

The Base interface of the SciML ecosystem

Modelingtoolkitstandardlibrary.jl ⭐ 89

A standard library of components to model the world and beyond

Diffeqparamestim.jl ⭐ 60

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

Diffeqphysics.jl ⭐ 47

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

Geometricintegrators.jl ⭐ 46

Geometric Numerical Integration in Julia

Globalsensitivity.jl ⭐ 41

Robust, Fast, and Parallel Global Sensitivity Analysis (GSA) in Julia

Dassl.jl ⭐ 31

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

Parameterestimation.jl ⭐ 24

ParameterEstimation.jl is a Julia package for estimating parameters and initial conditions of ODE models given measurement data.

Control_neuralode ⭐ 9

On the use of NeuralODEs as optimal control policies: I.O. Sandoval, P. Petsagkourakis, E. A. del Rio-Chanona, “Neural ODEs as Feedback Policies for Nonlinear Optimal Control” The 22nd World Congress of the International Federation of Automatic Control (IFAC 2023)

Sbml2julia ⭐ 5

A tool to for optimizing parameters of ordinary differential equation (ODE) models. SBML2Julia translates a model from SBML/PEtab format into Julia for Mathematical Programming (JuMP), performs the optimization task and returns the results.

Sbmlinterface.jl ⭐ 5

Interface between the Systems Biology Markup Language and Julia

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