kotlingrad
🧩 Shape-Safe Symbolic Differentiation with Algebraic Data Types (by breandan)
jcheatsheet | kotlingrad | |
---|---|---|
4 | 3 | |
5 | 508 | |
- | - | |
0.0 | 3.8 | |
about 2 years ago | about 1 year ago | |
HTML | Kotlin | |
- | Apache License 2.0 |
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.
jcheatsheet
Posts with mentions or reviews of jcheatsheet.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-03-13.
-
J language cheatsheet (or an alternative view for NuVoc)
I filed an issue in the repo. Do I understand the problem correctly? I think "execute u repeatedly until v^:_ returns 0" should be replaced with "execute u repeatedly until v returns 0", right?
Hi folks. The repo is here, and here's a quote from it:
kotlingrad
Posts with mentions or reviews of kotlingrad.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-12-25.
-
Trade-Offs in Automatic Differentiation: TensorFlow, PyTorch, Jax, and Julia
and that there is a mature library for autodiff https://github.com/breandan/kotlingrad
- Show HN: Shape-Safe Symbolic Differentiation with Algebraic Data Types
- Kotlin∇: Type-safe Symbolic Differentiation for the JVM
What are some alternatives?
When comparing jcheatsheet and kotlingrad you can also consider the following projects:
AOC2021-BQN - new repository is at razetime/aoc.
lets-plot-kotlin - Grammar of Graphics for Kotlin
kmath - Kotlin mathematics extensions library
kinference - Running ONNX models in vanilla Kotlin
uiua - A stack-based array programming language
dex-lang - Research language for array processing in the Haskell/ML family
kotlindl - High-level Deep Learning Framework written in Kotlin and inspired by Keras