A Programming Language for Deep Learning
-
Updated
May 10, 2018 - Haskell
#
automatic-differentiation
Here are 11 public repositories matching this topic...
Heterogeneous automatic differentiation ("backpropagation") in Haskell
deep-learning neural-network graph automatic-differentiation gradient-descent backpropagation backprop
-
Updated
Jun 5, 2025 - Haskell
Higher Order Reverse Derivatives Efficiently - Automatic Differentiation library. See http://arxiv.org/abs/2507.12640.
-
Updated
Nov 19, 2025 - Haskell
DSL for forward and reverse mode automatic differentiation in Haskell. Port of DiffSharp.
-
Updated
Jun 27, 2019 - Haskell
Automatic Differentiation using Pseudo Lenses. Neat.
-
Updated
Feb 7, 2020 - Haskell
Small autodiff lib and a simple working feedforward neural net in Haskell on top of it, from scratch, zero-deps.
-
Updated
Jun 21, 2024 - Haskell
Reverse-mode automatic differentiation with delimited continuations
-
Updated
Jul 3, 2023 - Haskell
Code for understanding automatic differentiation.
-
Updated
Jul 24, 2022 - Haskell
Several Haskell packages for numerical optimizations.
-
Updated
Mar 3, 2025 - Haskell
Domain Specific Language to perform Automatic Differentiation on Higher Order functions.
-
Updated
Feb 11, 2021 - Haskell
Github page for my Masters Thesis.
-
Updated
Jun 13, 2022 - Haskell
Improve this page
Add a description, image, and links to the automatic-differentiation topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the automatic-differentiation topic, visit your repo's landing page and select "manage topics."