Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks

26 March 2020

Papers citing "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks"

5 / 5 papers shown

Title
How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing Keke Huang Yu Guang Wang Ming Li Pietro Lió 35 17 0 21 May 2024
Parallel and Distributed Graph Neural Networks: An In-Depth Concurrency Analysis Maciej Besta Torsten Hoefler GNN 32 55 0 19 May 2022
RA-GCN: Graph Convolutional Network for Disease Prediction Problems with Imbalanced Data Mahsa Ghorbani Anees Kazi M. Baghshah Hamid R. Rabiee Nassir Navab 19 72 0 27 Feb 2021
Interpretable Stability Bounds for Spectral Graph Filters Henry Kenlay D. Thanou Xiaowen Dong 6 39 0 18 Feb 2021
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 1,809 0 25 Nov 2016