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. 2207.04396
  4. Cited By
Graph Generative Model for Benchmarking Graph Neural Networks

Graph Generative Model for Benchmarking Graph Neural Networks

10 July 2022
Minji Yoon
Yue Wu
John Palowitch
Bryan Perozzi
Ruslan Salakhutdinov
ArXivPDFHTML

Papers citing "Graph Generative Model for Benchmarking Graph Neural Networks"

6 / 6 papers shown
Title
GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?
GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?
Mufei Li
Eleonora Kreacic
Vamsi K. Potluru
Pan Li
DiffM
11
7
0
20 Oct 2023
GraphWorld: Fake Graphs Bring Real Insights for GNNs
GraphWorld: Fake Graphs Bring Real Insights for GNNs
John Palowitch
Anton Tsitsulin
Brandon Mayer
Bryan Perozzi
GNN
180
68
0
28 Feb 2022
IGLU: Efficient GCN Training via Lazy Updates
IGLU: Efficient GCN Training via Lazy Updates
S. Narayanan
Aditya Sinha
Prateek Jain
Purushottam Kar
Sundararajan Sellamanickam
BDL
29
9
0
28 Sep 2021
Releasing Graph Neural Networks with Differential Privacy Guarantees
Releasing Graph Neural Networks with Differential Privacy Guarantees
Iyiola E. Olatunji
Thorben Funke
Megha Khosla
27
44
0
18 Sep 2021
GraphDF: A Discrete Flow Model for Molecular Graph Generation
GraphDF: A Discrete Flow Model for Molecular Graph Generation
Youzhi Luo
Keqiang Yan
Shuiwang Ji
DRL
157
185
0
01 Feb 2021
Junction Tree Variational Autoencoder for Molecular Graph Generation
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
208
1,205
0
12 Feb 2018
1