Understanding Graph Neural Networks from Graph Signal Denoising Perspectives

8 June 2020

Papers citing "Understanding Graph Neural Networks from Graph Signal Denoising Perspectives"

6 / 6 papers shown

Title
From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited Zheng Wang H. Ding L. Pan Jianhua Li Zhiguo Gong Philip S. Yu GNN 31 5 0 24 Sep 2023
What Has Been Enhanced in my Knowledge-Enhanced Language Model? Yifan Hou Guoji Fu Mrinmaya Sachan KELM 35 1 0 02 Feb 2022
Graph Denoising with Framelet Regularizer Bingxin Zhou Ruikun Li Xuebin Zheng Yu Guang Wang Junbin Gao 21 14 0 05 Nov 2021
Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns Susheel Suresh Vinith Budde Jennifer Neville Pan Li Jianzhu Ma 37 131 0 11 Jun 2021
A Unified View on Graph Neural Networks as Graph Signal Denoising Yao Ma Xiaorui Liu Tong Zhao Yozen Liu Jiliang Tang Neil Shah AI4CE 36 176 0 05 Oct 2020
Graph signal processing for machine learning: A review and new perspectives Xiaowen Dong D. Thanou Laura Toni M. Bronstein P. Frossard 24 154 0 31 Jul 2020