Error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations, operations with arrays, and numerical integration.

Plotting for Julia based on matplotlib.pyplot

Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.

Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.

Climate Machine: an Earth System Model that automatically learns from data

Statistical plotting recipes for Plots.jl

Density-functional toolkit

Probabilistic programming via source rewriting

Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization

Iterative algorithms for solving linear systems, eigensystems, and singular value problems

Molecular simulation in Julia

Computational geometry in Julia

Binary Dependency Builder for Julia

"Distributions" that might not add to one.

Julia package with selected functions in the R package `rethinking`. Used in the SR2... projects.

Filter design, periodograms, window functions, and other digital signal processing functionality

Plotting for Julia based on GR, a framework for visualisation applications

Time series toolkit for Julia

Visualization of Julia profiling data

A comprehensive open source computer algebra system for computations in algebra, geometry, and number theory.

Probabilistic Programming with Gaussian processes in Julia

Surrogate modeling and optimization for scientific machine learning (SciML)

A fast trajectory optimization library written in Julia

A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.

A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.

Modeling and simulation of multidomain engineering systems

Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R

Call R from Julia

Convex optimization for fun and profit. (Now in Julia!)

The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems

A Julia package for Gaussian Processes

A differentiable physics engine for robotics

Data structures in Julia to enable power systems analysis. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.

Polynomial manipulations in Julia

A Julia package to perform Bifurcation Analysis

A JuMP extension for Stochastic Dual Dynamic Programming

Julia implementation of various rigid body dynamics and kinematics algorithms

Automatic Differentiation Library for Computational and Mathematical Engineering

Linear operators for discretizations of differential equations and scientific machine learning (SciML)

GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem