From 524db514bf8d1c8f26ebf2e98599f67883fb26ea Mon Sep 17 00:00:00 2001 From: LordSaumya <68504323+LordSaumya@users.noreply.github.com> Date: Tue, 24 Dec 2024 15:38:11 +0530 Subject: [PATCH] Add Readme to crate directory --- rusty_kan/README.md | 27 +++++++++++++++++++++++++++ 1 file changed, 27 insertions(+) create mode 100644 rusty_kan/README.md diff --git a/rusty_kan/README.md b/rusty_kan/README.md new file mode 100644 index 0000000..18e2631 --- /dev/null +++ b/rusty_kan/README.md @@ -0,0 +1,27 @@ +# Rusty-KAN + +Kolmogorov-Arnold Networks are a type of neural network that is based on the [Kolmogorov-Arnold representation theorem](https://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Arnold_representation_theorem). Essentially, it states that any continuous function can be represented as a composition of a finite number of univariate functions. + +Therefore, a KAN is a neural network where the activation functions are placed on the edges and act as learnable weights for the network. The nodes simply sum the incoming activations. + +For example, see the following image, which shows how functions are composed in a KAN to approximate continuous functions: +![alt text](image.png) + +This is the basis of the Rusty-KAN library, which is a Rust implementation of the KAN. + +## Installation + +To install Rusty-KAN, simply add the following line to your `Cargo.toml` file: + +```toml +[dependencies] +rusty-kan = "0.1.0" +``` + +## References + +- [Kolmogorov-Arnold representation theorem](https://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Arnold_representation_theorem) + +- [KAN: Kolmogorov-Arnold Networks](https://arxiv.org/abs/2404.19756) + +- [pykan](https://github.com/KindXiaoming/pykan)