EnzymeAD/Enzyme.jl

Forward Mode Automatic Differentiation for Julia

21st century AD

High-performance automatic differentiation of LLVM and MLIR.

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

Elegant and Performant Deep Learning

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.

Efficiently computes derivatives of NumPy code.

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

Julia package for tensor contractions and related operations