7 projects
JAX
JAX is a high-performance numerical computing and machine learning library that combines Numpy's familiar API with GPU and TPU hardware acceleration. It features automatic differentiation, just-in-time compilation, and enables writing transformable numerical programs.
6,112
1,124
$20M
Enzyme Automatic Differentiator
Enzyme is an automatic differentiation tool that performs reverse-mode AD by using LLVM compiler infrastructure to differentiate programs in languages like Julia, C/C++, and Fortran. It enables efficient gradient computation for machine learning and scientific computing applications.
363
128
$1.8M
ChainRules
forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs
SciMLBase
The Base interface of the SciML ecosystem
Zygote.jl
21st century AD