#Autodiff
Showing 16 of 16 repositories tagged #autodiff, ranked by stars
Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.
Source-to-Source Debuggable Derivatives in Pure Python
Deep learning in Rust, with shape checked tensors and neural networks
End-to-end Generative Optimization for AI Agents
DiffSharp: Differentiable Functional Programming
Betty: an automatic differentiation library for generalized meta-learning and multilevel optimization
An interface to various automatic differentiation backends in Julia.
A JIT compiler for hybrid quantum programs in PennyLane
Autodifferentiation package in Rust.
A minimalist deep learning library written from scratch in Python
An experimental deep learning framework for Nim based on a differentiable array programming language
Born is a modern ML framework for Go — train and deploy models as single binaries. Pure Go, zero CGO, GPU accelerated.
Geometry processing utilities compatible with jax for autodifferentiation.
Сustom torch style machine learning framework with automatic differentiation implemented on numpy, allows build GANs, VAEs, etc.
A toy deep learning framework implemented in pure Numpy from scratch. Aka homemade PyTorch lol.
Automatic panorama stitching with automatic camera calibration/distortion estimation