📍 A Swift fork working towards Enzyme integration
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Updated
Mar 8, 2023 - C++
📍 A Swift fork working towards Enzyme integration
Differentiable computing on R^N metric spaces
Simple automatic differentiation tool.
Automatic differentiation: A tool that allows you to calculate multivariable equations, vectors, matrices, and more. All done in C++, no libraries!
A wrapper around R's optimisation routines where function gradients are computed with auto-diff
Reverse-mode autodiff for Clojure
Some deep learning library, cleaner than the last ones, but not faster
Neural networks and backprop in Java
Lightweight automatic differentiation and error propagation library
TensorFlow implementation of differentiable LQ matrix decomposition for all matrix orders.
A simple library for building computational graphs with autodiff support.
A simple and pythonic deep learning framework
Differentiable reparameterization of matrices with orthogonal columns.
Automatic differentiation in Rust for educational purposes. Autograd / tinygrad / micrograd / gradients.
A simple automatic differentiation library written in Go
A tiny reverse-mode autodiff and neural network library
Implementation of Forward Automatic Differentiation of Real Valued Functions with multiple threads
Tiny automatic differentiation (autodiff) engine for NumPy tensors implemented in Python.
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