ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2304.01235
  4. Cited By
How Graph Structure and Label Dependencies Contribute to Node
  Classification in a Large Network of Documents

How Graph Structure and Label Dependencies Contribute to Node Classification in a Large Network of Documents

3 April 2023
Pirmin Lemberger
Antoine Saillenfest
    GNN
ArXivPDFHTML

Papers citing "How Graph Structure and Label Dependencies Contribute to Node Classification in a Large Network of Documents"

3 / 3 papers shown
Title
Beyond Low-frequency Information in Graph Convolutional Networks
Beyond Low-frequency Information in Graph Convolutional Networks
Deyu Bo
Xiao Wang
C. Shi
Huawei Shen
GNN
87
556
0
04 Jan 2021
Multi-scale Attributed Node Embedding
Multi-scale Attributed Node Embedding
Benedek Rozemberczki
Carl Allen
Rik Sarkar
GNN
145
833
0
28 Sep 2019
Geometric deep learning on graphs and manifolds using mixture model CNNs
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
1,811
0
25 Nov 2016
1