| title | Automatic differentiation |
|---|
- Automatic Differentiation in Machine Learning: a Survey
- autodiff - C++17 library that uses modern and advanced programming techniques to enable automatic computation of derivatives in an efficient and easy way.
- Automatic Differentiation via Contour Integration (2020) (Article) (HN)
- Taichi - Data-oriented programming language. Decouples computation from data organization. (Code) (Article) (Awesome)
- Demystifying Differentiable Programming: Shift/Reset the Penultimate Backpropagator (2019)
- Forward-mode Automatic Differentiation for TensorFlow
- Automatic Differentiation tools for both forward and reverse mode written for R6RS Scheme
- From scratch: reverse-mode automatic differentiation (in Python) (2020) (HN)
- ADMB Project - Supports the application of automatic differentiation (AD) for solutions to non-linear statistical modeling and optimization problems. (Web)
- GTN: Automatic Differentiation with WFSTs (weighted finite-state transducers)
- Differentiation with higher infinitesimals - Exploring connections between automatic differentiation and smooth infinitesimal analysis, or smooth algebras.
- AD4SM.jl - Automatic Differentiation for Solid Mechanics.
- ceviche - Electromagnetic Simulation Tools + Automatic Differentiation.
- Tangent - Source-to-Source Debuggable Derivatives in Pure Python.
- Symbolic and Automatic Differentiation of Languages (2021) (Code)
- oxide-enzyme - Enzyme integration into Rust. State-of-the-art AutoDiff in Rust. (Reddit)
- simplegrad - Simple reverse mode automatic differentiation of scalar values in JS.
- Downhill - Reverse mode automatic differentiation in Haskell. (Docs) (Tweet)
- Trade-Offs in Automatic Differentiation: TensorFlow, PyTorch, Jax, and Julia (2021) (HN)
- Decomposing reverse-mode automatic differentiation (2021)
- RustAD - Rust Auto-Differentiation.
- Storchastic - PyTorch library for stochastic gradient estimation in Deep Learning.
- AbstractDifferentiation - Abstract interface for automatic differentiation.
- ad - Package that provides an intuitive API for Automatic Differentiation (AD) in Haskell.
- Automatic Differentiation: Inverse Accumulation Mode (2019)
- ImplicitDifferentiation.jl - Automatic differentiation of implicit functions.
- Pymanopt - Python toolbox for optimization on Riemannian manifolds with support for automatic differentiation.
- Automatic Differentiation Handbook
- Differentiable Programming – A Simple Introduction (HN)
- Aude - Automated differentiation solver with a Lisp-like functional programming language.
- PyNeuraLogic - Lets you use Python to write Differentiable Logic Programs.
- dCpp - Automatic differentiation in C++. Infinite differentiability of conditionals, loops, recursion and all things C++.
- ad-delcont - Reverse-mode automatic differentiation with delimited continuations.
- Dynamic Automatic Differentiation in Rust
- The simple essence of automatic differentiation
- TinyAD - C++ header-only library for second-order automatic differentiation.
- Betty - Automatic differentiation library for generalized meta-learning and multilevel optimization.
- Randomized Automatic Differentiation (2020)
- Differentiable programming from scratch (2022) (HN)
- Discussion on Solving Partial Differential Equations using Neural Networks
- Automatic Differentiation in 38 lines of Haskell (HN)
- Automatic Differentiation: Forward and Reverse (2022) (HN)