| ad | grenade | |
|---|---|---|
| 6 | 5 | |
| 364 | 1,440 | |
| - | - | |
| 5.9 | 5.6 | |
| about 21 hours ago | 5 months ago | |
| Haskell | Haskell | |
| BSD 3-clause "New" or "Revised" License | BSD 2-clause "Simplified" License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ad
Posts with mentions or reviews of ad.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-02-27.
-
Is there an implementation of The Simple Essence of Automatic Differentiation (2018)?
Maybe ad?
-
Backpropagation and Accelerate
I’ll also link the ad package here in case someone can speak to its value over backprop https://github.com/ekmett/ad
-
[ad] Haskell Revitalisation
Apologies in advance for disappointing a few people but the [ad] part in the title doesn't mean Automatic Differentiation but rather means "advertisement".
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Let's Program a Calculus Student II: Turning Symbolic Differentiation Automatic
Hi everybody! A couple weeks ago, I made a blog post talking about how recursion and pattern matching could be used to translate Calculus formulas into Haskell. This is a follow-up exploring how to use automatic differentiation to calculate those same derivatives as an example of cool stuff that polymorphism allows us to do. (I learned this idea from the ad package and really fell in love with how elegant it is)
- Monthly Hask Anything (March 2022)
- What are some ways I could tickle my (beginner) haskell-brain with something *useful*?
grenade
Posts with mentions or reviews of grenade.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-23.
-
Haskell deep learning tutorials [Blog]
Grenade is fun, but it does not support CUDA, so it will limit you. I would say that this was a great experiment that has influenced the Hasktorch library in different ways (let me know if I am wrong).
- Dhall: A Gateway Drug to Haskell
-
Haskell for Artificial Intelligence?
FWIW there's an interesting library called grenade which offers nice types for constructing neural nets. I haven't used it, and this is not my areas of expertise, but it looks cool!
-
Rank 3 Stencils for "Efficient Parallel Stencil Convolution in Haskell" (Repa)
When I wrote grenade I used the im2col trick to turn convolutions into a single matrix multiplication, which could then be done in hmatrix.
- What are some ways I could tickle my (beginner) haskell-brain with something *useful*?
What are some alternatives?
When comparing ad and grenade you can also consider the following projects:
modular-arithmetic - A useful type for working with integers modulo some constant.
hasktorch - Tensors and neural networks in Haskell
roots - 1-dimensional root-finding algorithms in Haskell
liblinear-enumerator - Haskell bindings to liblinear
nimber - Finite nimber arithmetic
simple-neural-networks - Simple parallel neural networks implementation in pure Haskell
moving-averages
CV - Haskell wrappers and utilities for OpenCV machine vision library
search - infinite search in finite time with Hilbert's epsilon
nn - A tiny neural network 🧠
gamma - Haskell implementation of gamma and incomplete gamma functions
hnn - haskell neural network library