Highly optimized K-SVD implementation in Julia, with several parallelization techniques available.

TimeArrays simplifies working with time series data. It offers features like basic math operations, sliding window techniques, data resampling, and handling of missing values

Efficient transducers for Julia

Truncated Power Series for Julia

Lambert W mathematical function

Taylor-mode automatic differentiation for higher-order derivatives

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:abacus: A mathematics library

Julia interface to hypre linear solvers (https://github.com/hypre-space/hypre)

A Julia package for the creation, manipulation and analysis of the structure, dynamics and functions of multilayer graphs.

Create truth tables in Julia!

Analysis of complex surveys

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

Automatic differentiation of implicit functions

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A fully `Distributions.jl`-compliant copula package

Julia implementations of symbolic integration algorithms

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Bessel functions for real arguments and orders

Automatic Finite Difference PDE solving with Julia SciML

Groebner bases in (almost) pure Julia

Solve Fractional Differential Equations using high performance numerical methods

Graph data structures with multiple heterogeneous metadata for Graphs.jl.

Edge-weighted graphs compatible with Graphs.jl

An optimized graphs package for the Julia programming language

Fowler–Noll–Vo hash functions Julia package

Types and constructors for spatially referenced graphs.

SymbolicNumericIntegration.jl: Symbolic-Numerics for Solving Integrals

Sparse tensors in Julia and more! Datastructure-driven array programing language.

LinearSolve.jl: High-Performance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, add preconditioners, and all in one interface.

No need to train, he's a smooth operator

Approximations for Gaussian processes: sparse variational inducing point approximations, Laplace approximation, ...

Optimal addition-chain exponentiation for Julia

A Julia package for Deep Backwards Stochastic Differential Equation (Deep BSDE) and Feynman-Kac methods to solve high-dimensional PDEs without the curse of dimensionality

A package for representing playing cards for card games.

Tools for working with Fourier space.

Core functions for the Julia (2nd) edition of the text Fundamentals of Numerical Computation, by Driscoll and Braun.

A latex math mode engine in pure Julia.

An abstract interface for automatic differentiation.

A Julia package for classical orthogonal polynomials and expansions