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

A Julia package for describing domains as continuous sets of elements

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

Missing value support for Julia

Julia Wrappers for the arpack-ng Fortran library

A Julia package for calculating hypergeometric functions

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

Implementation of advanced Sequential Monte Carlo and particle MCMC algorithms

An implementation of an LRU Cache in Julia

Convenient macros for in-place matrix operations in Julia

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.

Faster closure variable capture

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

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Zlib codecs for TranscodingStreams.jl.

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Interface for arithmetics on mutable types in Julia

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

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

Calculating contour curves for 2D scalar fields in Julia

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)

Lightweight robust covariance estimation in Julia

Wrapper around mbedtls

Logging sinks and utilites for interactive terminals

Truncated singular value decomposition with partial reorthogonalization

A common framework for implementing and using log densities for inference.