Abstract: Recently, polynomial graph filter learning (PGFL) has demonstrated promising performance for modeling graph signals in Graph Neural Networks (GNNs) on both homophilic and heterophilic graphs ...

Abstract: Understanding the underlying graph structure of a nonlinear map over a particular domain is essential in evaluating its potential for real applications. In this paper, we investigate the ...

This project is a Graph Plotting Application with a graphical user interface built using Tkinter and Matplotlib. It is designed for users without programming experience to easily create and customize ...

This repository contains a PyTorch implementation of ICLR 2024 paper "PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters". We provide the small datasets in the folder 'data' ...