Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.

Julia bindings for the Enzyme automatic differentiator

Update immutable data

Implementation of domain-specific language (DSL) for dynamic probabilistic programming

Common functional iterator patterns

Symbolic programming for the next generation of numerical software

Symbolic expressions, rewriting and simplification

Bayesian inference with probabilistic programming.

Calculating contour curves for 2D scalar fields in Julia

Print data in formatted tables.

Implementation of variational Bayes inference algorithms

Simple, consistent interfaces for any codec.

Root finding functions for Julia

The Base interface of the SciML ecosystem

Basic interface for manifolds in Julia

Powerful convenience for Julia visualizations and data analysis

Primitives for construction of objects

Filter design, periodograms, window functions, and other digital signal processing functionality

Simple, fast, column-based storage for data analysis in Julia

Manifolds.jl provides a library of manifolds aiming for an easy-to-use and fast implementation.

AD-backend agnostic system defining custom forward and reverse mode rules. This is the light weight core to allow you to define rules for your functions in your packages, without depending on any particular AD system.

Forward Mode Automatic Differentiation for Julia

Forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs

SciMLOperators.jl: Matrix-Free Operators for the SciML Scientific Machine Learning Common Interface in Julia

Convert julia objects to LaTeX equations, arrays or other environments.

Julia implementation of Data structures

A Julia interface to the NLopt nonlinear-optimization library

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

Julia macro for re-exporting one module from another

Julia bindings to the FFTW library for fast Fourier transforms

Julia wrapper for the LLVM C API

Formatted output of timed sections in Julia

Julia functional programming infrastructures and metaprogramming facilities

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

A Julia package for fitting (statistical) mixed-effects models

Mathematical functions related to statistics.

Abstract types and interfaces for Markov chain Monte Carlo methods

Heterogeneous programming in Julia

Abstract julia interfaces for working with trees

A Julia package for defining and working with linear maps, also known as linear transformations or linear operators acting on vectors. The only requirement for a LinearMap is that it can act on a vector (by multiplication) efficiently.