Repo for CLAR: Complement LAplacian Regularization

Thanks for your interest in our ICDMW'22 paper: Improving Your Graph Neural Networks: A High-Frequency Booster. https://arxiv.org/abs/2210.08251

A gentle reminder for CLAR repository

We publicize the essential three Python files for a better understanding of our submission and to ensure reproducibility.

• train_reg.py: The entrance of our project, where the annotates for the regularization methods are essential.
• utils.py: It includes data-processing functions, and all the regularization methods, e.g., MADReg, P_reg, CLAR_reg, etc.
• model.py: All the baselines are reproduced in this file.