Deep learning in Rust, with shape checked tensors and neural networks
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Updated
Mar 2, 2024 - Rust
Deep learning in Rust, with shape checked tensors and neural networks
Tensors and differentiable operations (like TensorFlow) in Rust
A minimal OpenCL, CUDA, Vulkan and host CPU array manipulation engine / framework.
A neural network, and tensor dynamic automatic differentiation implementation for Rust.
Define-by-run arbitrary higher order autodiff for scalars in Rust. Deferred: tensor calculus implementation.
Deep Learning Framework Written in Rust
Automatic differentiation for tensor operations
(WIP) Simple Deep Learning Framework and Auto Differentiation Engine in Rust
A toy neural networks library with zero* dependencies
A minimal autograd implementation in rust
Automatic differentiation in Rust for educational purposes. Autograd / tinygrad / micrograd / gradients.
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
RUNE: RUsty Neural Engine
A tiny autograd engine for learning purposes in Rust
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