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. 2208.02435
  4. Cited By
Node Copying: A Random Graph Model for Effective Graph Sampling

Node Copying: A Random Graph Model for Effective Graph Sampling

4 August 2022
Florence Regol
Soumyasundar Pal
Jianing Sun
Yingxue Zhang
Yanhui Geng
Mark J. Coates
ArXivPDFHTML

Papers citing "Node Copying: A Random Graph Model for Effective Graph Sampling"

4 / 4 papers shown
Title
Are Defenses for Graph Neural Networks Robust?
Are Defenses for Graph Neural Networks Robust?
Felix Mujkanovic
Simon Geisler
Stephan Günnemann
Aleksandar Bojchevski
OOD
AAML
19
56
0
31 Jan 2023
Robust Node Classification on Graphs: Jointly from Bayesian Label
  Transition and Topology-based Label Propagation
Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation
Jun Zhuang
M. Hasan
23
20
0
21 Aug 2022
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,134
0
06 Jun 2015
A survey of statistical network models
A survey of statistical network models
Anna Goldenberg
A. Zheng
S. Fienberg
E. Airoldi
120
976
0
29 Dec 2009
1