An extensible framework for geospatial data science and geostatistical modeling fully written in Julia

Julia implementation of QuantEcon routines

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.

Metaprogramming tools for DataFrames

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

Julia package for tensor contractions and related operations

Statistical plotting recipes for Plots.jl

Density-functional toolkit

Play atmospheric modelling like it's LEGO.

Julia library for plotting with plotly.js

Probabilistic programming via source rewriting

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

Print data in formatted tables.

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

Computational geometry in Julia

Molecular simulation 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

A package that makes it trivial to create and evaluate machine learning pipeline architectures.

Time series toolkit for Julia

Geometric Deep Learning for Flux

Visualization of Julia profiling data

Probabilistic Programming with Gaussian processes 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 fast trajectory optimization library written in Julia

Surrogate modeling and optimization for scientific machine learning (SciML)

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.

Computer vision models for Flux

Modeling and simulation of multidomain engineering systems

Call R from 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