Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.

Deep learning in Rust, with shape checked tensors and neural networks

Tensors and differentiable operations (like TensorFlow) in Rust

l2 is a fast, Pytorch-style Tensor+Autograd library written in Rust

N-dimensional matrix class for Rust

A Rust Library for High-Performance Tensor Exchange with Python

A neural network, and tensor dynamic automatic differentiation implementation for Rust.

Simplistic API for deep learning tensor operations

DLPack safe Rust binding

Rust accelerated contraction ordering primitives for tensor networks and einsums

DEPRECATED: this repo has been moved into https://github.com/dmlc/tvm/blob/master/rust

Automatic differentiation for tensor operations

Acme aims to be a complete auto differentiation system written in Rust.

Tensor library in Rust.

This is a rust implementation of tensorflow obviously it's not as advanced but it gets the job done 😅

🦀 RUNE: RUsty Neural Engine

RUNE: RUsty Neural Engine

ndtensor is designed to be a flexible and powerful tensor library for Rust

Novigrad is an automatic differentiation engine with a forward mode and a backward mode. It aims to be a minimalistic neural network framework written in Rust. It's a work-in-progress.

Minimalist ML framework for Rust