-

-

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

A Julia package for describing domains as continuous sets of elements

Missing value support for Julia

A Julia package for calculating hypergeometric functions

Geometry types for Julia

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.

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

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

Faster closure variable capture

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

Extra sorting algorithms extending Julia's sorting API

Fast complex polynomial root finder, with support for arbitrary precision calculations

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

Static types useful for dispatch and generated functions.

Zlib codecs for TranscodingStreams.jl.

Makes Julia's package extensions backwards compatible

-

Interface for arithmetics on mutable types in Julia

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

Bijection datatype for Julia.

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

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

-

Repository for automatic differentiation backend types

Positive-definite "approximations" to matrices

A Julia package to provide C and Python-like formatting support

Naïve combined subexpression elimination in Julia

Direct solution of large sparse systems of linear algebraic equations in pure Julia

Common interface for symbolic terms, allowing symbolic libraries with different underlying structures to interact and convert

Treat colors as if they are n-vectors for the purposes of arithmetic