Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.

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

Rust ML toolkit. Prototype to production. All in one.

A learning-focused, high-performance tensor computation library built from scratch in Rust, featuring automatic differentiation and CPU/CUDA backends.

N-dimensional matrix class for Rust

An n-dimensional rust tensor library

A Rust Library for High-Performance Tensor Exchange with Python

A high performance N-dimensional array library for Rust

A user-friendly ML framework built in Rust

Simplistic API for deep learning tensor operations

Rust accelerated contraction ordering primitives for tensor networks and einsums

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

High-performance Machine Learning, Dynamic Auto-Differentiation and Tensor Algebra crate for Rust

DLPack safe Rust binding

TensorLogic compiles logical rules (predicates, quantifiers, implications) into tensor equations (einsum graphs) with a minimal DSL + IR, enabling neural/symbolic/probabilistic models within a unified tensor computation framework.

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

An animal can do training and inference every day of its existence until the day of its death. A forward pass is all you need.