Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms

High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.

A combinatorics library for Julia

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

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

Convenient input and display of LaTeX equation strings for the Julia language

Color manipulation utilities for Julia

Reduce time-to-first-execution of Julia code

Neural Network primitives with multiple backends

Performant arrays where each dimension can have a named axis with values

Abstract julia interfaces for working with trees

Implementation of normalising flows and constrained random variable transformations

Fortran-like arrays with arbitrary, zero or negative starting indices.

Lazy code loading for Julia

BlockArrays for Julia

Julia wrappers of SymEngine

Colorschemes, colormaps, gradients, and palettes

Julia package for lazily representing matrices filled with a single entry

A Julia package for solving systems of polynomials via homotopy continuation.

Kernel density estimators for Julia

Update immutable data

Conda managing Julia binary dependencies

Update deeply nested immutable structs.

An interface to various automatic differentiation backends in Julia.

Julia macro for re-exporting one module from another

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

Julia package for 1-d and 2-d splines

Reusable compiler infrastructure for Julia GPU backends.

Simple Traits for Julia

An enhancement to julia piping syntax

Common functional iterator patterns

Automatic differentiation of Distributions using Tracker, Zygote, ForwardDiff and ReverseDiff

Einstein summation notation in Julia

Colored and styled strings for terminals.

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Generic numerical linear algebra in Julia

Math with more good bits

A Julia package for strided array views and efficient manipulations thereof

Compatibility across Julia versions

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)