RandAlign: A Parameter-Free Method for Regularizing Graph Convolutional Networks

15 April 2024

Papers citing "RandAlign: A Parameter-Free Method for Regularizing Graph Convolutional Networks"

5 / 5 papers shown

Title
Optimization-Induced Graph Implicit Nonlinear Diffusion Qi Chen Yifei Wang Yisen Wang Jiansheng Yang Zhouchen Lin DiffM 45 32 0 29 Jun 2022
Graph Neural Networks with Learnable Structural and Positional Representations Vijay Prakash Dwivedi A. Luu T. Laurent Yoshua Bengio Xavier Bresson GNN 182 304 0 15 Oct 2021
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 181 907 0 02 Mar 2020
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 226 1,935 0 09 Jun 2018
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 234 1,801 0 25 Nov 2016