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

Bayesian inference with probabilistic programming.

Reusable compiler infrastructure for Julia GPU backends.

Repository for automatic differentiation backend types

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

Implementation of domain-specific language (DSL) for dynamic probabilistic programming

A machine learning compiler for GPUs, CPUs, and ML accelerators

Implementation of normalising flows and constrained random variable transformations

A faster approximation to floating point power, at the trade-off of some accuracy

Portable (POSIX/Windows/Emscripten) thread pool for C/C++

Development repository for the Triton language and compiler

Functionality for modifying Julia package registry files

High-Performance Symbolic Regression in Python and Julia

The Julia Language: A fresh approach to technical computing.

AD x Turing.jl status

The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.

High accuracy derivatives, estimated via numerical finite differences (formerly FDM.jl)

C binding generator and Julia interface to libclang

Backward compatible ML compute opset inspired by HLO/MHLO

Explicitly Parameterized Neural Networks in Julia

Hybrid ML + physics model of the Earth's atmosphere

Collective communications library with various primitives for multi-machine training.

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.

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

The base package for Optimization.jl, containing the structs and basic functions for it.

Julia bindings to the FFTW library for fast Fourier transforms