Relax! Flux is the ML library that doesn't make you tensor

Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.

Bayesian inference with probabilistic programming.

Crafty statistical graphics for Julia.

A general-purpose probabilistic programming system with programmable inference

A Julia machine learning framework

21st century AD

An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations

Symbolic programming for the next generation of numerical software

A generic, simple and fast implementation of Deepmind's AlphaZero algorithm.

Optimization functions for Julia

A Julia package for probability distributions and associated functions.

Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

A Julia wrapper for TensorFlow

Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)

Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

Award winning software library for nonlinear dynamics and nonlinear timeseries analysis

⚡ Single-pass algorithms for statistics

Parallel analytical database in pure Julia

Agent-based modeling framework in Julia

Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.

Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.

Grid-based approximation of partial differential equations in Julia

MDPs and POMDPs in Julia - An interface for defining, solving, and simulating fully and partially observable Markov decision processes on discrete and continuous spaces.

A framework for out-of-core and parallel execution

Repository of best practices for deep learning in Julia, inspired by fastai

Generalized linear models in Julia

Distributed High-Performance Symbolic Regression in Julia

Julia package for function approximation

High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)

Library for the numerical simulation of closed as well as open quantum systems.

Trixi.jl: Adaptive high-order numerical simulations of conservation laws in Julia

Julia Implementation of Transformer models

Meta-package for data analysis in Julia, modeled after the R tidyverse.

A Control Systems Toolbox for Julia

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

Julia implementation of QuantEcon routines

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.