awesome-haskell-deep-learning
github.com/austinvhuang/awesome-haskell-deep-learning ↗In the tradition of "awesome" (curated) lists, this is a list of references and code for doing deep learning in Haskell.
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ArticlesTalksHaskell PackagesRelated Topics & Links
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Installation instructions →What's inside
Talks
- A Functional Reboot for Deep Learning (BOB 2019 Talk)
- Berlin Functional Programming Group: Hasktorch
- Keynote: Automatic Diferentiation for Dummies
- MuniHac 2020: Austin Huang - Hasktorch: Differentiable Functional Programming in Haskell
Hasktorch: Differentiable Functional Programming in Haskell
- NPFL Numerical Programming in Functional Languages (ICFP Session) 2018 Playlist
- The Simple Essence of Automatic Differentiation
Articles
- A Purely Functional Typed Approach to Trainable Models
- Backpack for deep learning
- Backprop as Functor: A compositional perspective on supervised learning
- Backpropogation is Just Steepest Descent with Automatic Differentiation
- Computing symbolic gradient vectors with plain Haskell
- DeepDarkFantasy: A Programming Language for Deep Learning
Haskell Packages
- arrayfire-haskellPackages Under Active Development
High-level Haskell bindings to the
- arrayfire-haskellArrayFirePackages Under Active Development
David Johnson
- backprop-hmatrixPackages Under Active Development
Justin Le
- convolutedLegacy Packages
Jonas Carpay
- deeplearning-hsLegacy Packages
- dexPackages Under Active Development
a research language for typed, functional array processing.
Showing a sample of 50 resources. View the full list on GitHub →