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Julia package for various special functions based on `log` and `exp`.

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

A Julia package for describing domains as continuous sets of elements

Missing value support for Julia

A Julia package for calculating hypergeometric functions

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

Julia library for the string interpolation of HTML and SVG

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

Resizeable multi-dimensional arrays for Julia

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

Basic numerical integration routines for presampled data.

Multivariate polynomials implementation of commutative and non-commutative variables

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

Faster closure variable capture

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

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

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

Extra sorting algorithms extending Julia's sorting API

Static types useful for dispatch and generated functions.

Flux's ex AD

Makes Julia's package extensions backwards compatible

Zlib codecs for TranscodingStreams.jl.

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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

Fixed-width string types for Julia

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

Bijection datatype for Julia.

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

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

Wrapper around mbedtls

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Positive-definite "approximations" to matrices