Julia library for optimal formatting of composite data structures

Optimisers.jl defines many standard optimisers and utilities for learning loops.

Missing value support for Julia

Julia Wrappers for the arpack-ng Fortran library

Julia interface for OSQP: The Operator Splitting QP Solver

A Julia package for calculating hypergeometric functions

Hyperparameter optimization algorithms for use in the MLJ machine learning framework

Base library providing vectorization-tools (ie, SIMD) that other libraries are built off of.

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

Fast and simple nonlinear solvers for the SciML common interface. Newton, Broyden, Bisection, Falsi, and more rootfinders on a standard interface.

Translate Julia to JavaScript

Use Optim to train Flux models and visualize loss landscapes

Delay differential equation (DDE) solvers in Julia for the SciML scientific machine learning ecosystem. Covers neutral and retarded delay differential equations, and differential-algebraic equations.

Scratch spaces for all your persistent mutable data needs

A Julia RNG with stable streams

Expression transformation package

A Julia package for representing block-banded matrices and banded-block-banded matrices

Faster closure variable capture

Ask the CPU for cache sizes, SIMD feature support, a running hypervisor, and more.

A Julia package for describing array layouts and more general fast linear algebra

Extra sorting algorithms extending Julia's sorting API

Julia math built-ins which return NaN and accumulator functions which ignore NaN

Static types useful for dispatch and generated functions.

Flux's ex AD

Makes Julia's package extensions backwards compatible

Zlib codecs for TranscodingStreams.jl.

Interface for arithmetics on mutable types in Julia

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Julia implementation for the BFloat16 number type

A pooled representation for arrays with few unique elements

A small package to simplify partial function application

Fixed-width integers similar to builtin ones

Fixed-width string types for Julia

Julia client for MLFlow.

A performant, 100% native-julia SHA1, SHA2, and SHA3 implementation

Calculating contour curves for 2D scalar fields in Julia

This package contains a macro for converting expressions to use muladd calls and fused-multiply-add (FMA) operations for high-performance in the SciML scientific machine learning ecosystem

Systems definitions in Julia

Boundary value problem (BVP) solvers for scientific machine learning (SciML)

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