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. 2010.03166
  4. Cited By
Accurate, Efficient and Scalable Training of Graph Neural Networks

Accurate, Efficient and Scalable Training of Graph Neural Networks

5 October 2020
Hanqing Zeng
Hongkuan Zhou
Ajitesh Srivastava
R. Kannan
Viktor Prasanna
    GNN
ArXivPDFHTML

Papers citing "Accurate, Efficient and Scalable Training of Graph Neural Networks"

4 / 4 papers shown
Title
DistGNN-MB: Distributed Large-Scale Graph Neural Network Training on x86
  via Minibatch Sampling
DistGNN-MB: Distributed Large-Scale Graph Neural Network Training on x86 via Minibatch Sampling
Md. Vasimuddin
Ramanarayan Mohanty
Sanchit Misra
Sasikanth Avancha
GNN
6
1
0
11 Nov 2022
T-EMDE: Sketching-based global similarity for cross-modal retrieval
T-EMDE: Sketching-based global similarity for cross-modal retrieval
Barbara Rychalska
Mikolaj Wieczorek
Jacek Dąbrowski
15
0
0
10 May 2021
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
273
2,878
0
15 Sep 2016
Benefits of depth in neural networks
Benefits of depth in neural networks
Matus Telgarsky
123
602
0
14 Feb 2016
1