The PyTorch implementation of Generative Pre-trained Transformers (GPTs) using Kolmogorov-Arnold Networks (KANs) for language modeling

Kolmogorov-Arnold Transformer: A PyTorch Implementation with CUDA kernel

This project is dedicated to the implementation and research of Kolmogorov-Arnold convolutional networks. The repository includes implementations of 1D, 2D, and 3D convolutions with different kernels, ResNet-like and DenseNet-like models, training code based on accelerate/PyTorch, as well as scripts for experiments with CIFAR-10 and Tiny ImageNet.

Implementation on how to use Kolmogorov-Arnold Networks (KANs) for classification and regression tasks.

TKAN: Temporal Kolmogorov-Arnold Networks

Improved LBFGS and LBFGS-B optimizers in PyTorch.

SigKAN: Signature-Weighted Kolmogorov-Arnold Networks for Time Series

This is the official repository for our paper KAGNNs: Kolmogorov-Arnold Networks meet Graph Learning.

Combine B-Splines (BS) and Radial Basis Functions (RBF) in Kolmogorov-Arnold Networks (KANs)

FC-KAN: Function Combinations in Kolmogorov-Arnold Networks

Short experiment with Deep Q-Learning + KAN to play Flappy Bird.

Testing KAN-based text generation GPT models

CoxKAN: Kolmogorov-Arnold Networks for Interpretable, High-Performance Survival Analysis

Code for Kolmogorov-Arnold Network for Quantum Architecture Search i.e., KANQAS

Semi-supervised learning with Generative Adversarial Networks (GANs) using Kolmogorov-Arnold Network Layers (KANLs)

KAN meets Gram Polynomials

Experiments on using Kolmogorov-Arnold Networks (KAN) on Graph Learning

KANs for text classification on GLUE tasks

Kolmogorov-Arnold Networks simple implementation using pytorch

Fourier-KAN, Lapalce-KAN and wavelet-KAN