Unitful Quantities in JAX
-
Updated
Aug 21, 2024 - Python
Unitful Quantities in JAX
Galactic and Gravitational Dynamics in Python (+ GPU and autodiff)
automatic differentiation library for Dart
skscope: Sparse-Constrained OPtimization via itErative-solvers
JutulDarcyRules: ChainRules extension to Jutul and JutulDarcy
Сustom torch style machine learning framework with automatic differentiation implemented on numpy, allows build GANs, VAEs, etc.
A lightweight auto-differentiation and backpropagation library written in python using numpy.
automatic differentiation made easier for C++
A simple Numpy & Python based auto differentiation system that supports visualization before and after back-propagation.
A WIP library for performing multi-root searching of one-dimensional transcendental equations using auto-differentiation in Rust
Minkowski Engine is an auto-diff neural network library for high-dimensional sparse tensors
A fast auto differentiation engine implemented in C++ 🔥
Library for auto differentiation based purely on NumPy
Define-by-run arbitrary higher order autodiff for scalars in Rust. Deferred: tensor calculus implementation.
MicrogradPlus is an educational project aiming to provide a simple, yet extensible, NumPy-based automatic differentiation library.
FastAD is a C++ implementation of automatic differentiation both forward and reverse mode.
Calculates partial derivatives of an input function.
[ ggml: Tensor library for machine learning ] written in zig.
Algorithmic differentiation with hyper-dual numbers in C++ and Python
Add a description, image, and links to the auto-differentiation topic page so that developers can more easily learn about it.
To associate your repository with the auto-differentiation topic, visit your repo's landing page and select "manage topics."