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.

Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)

Bayesian inference with probabilistic programming.

Crafty statistical graphics for Julia.

Powerful convenience for Julia visualizations and data analysis

A general-purpose probabilistic programming system with programmable inference

A Julia machine learning framework

21st century AD

Koç University deep learning framework.

Unicode-based scientific plotting for working in the terminal

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

🌊 Julia software for fast, friendly, flexible, ocean-flavored fluid dynamics on CPUs and GPUs

Forward Mode Automatic Differentiation for Julia

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

Julia Animations and Visualizations

Parallel analytical database in pure Julia

Macro(s) for vectorizing loops.

Agent-based modeling framework in Julia

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

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.

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

Fast and simple fluid simulator in Julia

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Physical quantities with arbitrary units

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