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. 2403.18142
  4. Cited By
HERTA: A High-Efficiency and Rigorous Training Algorithm for Unfolded
  Graph Neural Networks

HERTA: A High-Efficiency and Rigorous Training Algorithm for Unfolded Graph Neural Networks

26 March 2024
Yongyi Yang
Jiaming Yang
Wei Hu
Michal Dereziñski
ArXivPDFHTML

Papers citing "HERTA: A High-Efficiency and Rigorous Training Algorithm for Unfolded Graph Neural Networks"

14 / 14 papers shown
Title
Implicit vs Unfolded Graph Neural Networks
Implicit vs Unfolded Graph Neural Networks
Yongyi Yang
Tang Liu
Yangkun Wang
Zengfeng Huang
David Wipf
195
15
0
12 Nov 2021
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using
  Vector Quantization
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization
Mucong Ding
Kezhi Kong
Jingling Li
Chen Zhu
John P. Dickerson
Furong Huang
Tom Goldstein
GNN
MQ
66
49
0
27 Oct 2021
Elastic Graph Neural Networks
Elastic Graph Neural Networks
Xiaorui Liu
W. Jin
Yao Ma
Yaxin Li
Hua Liu
Yiqi Wang
Ming Yan
Jiliang Tang
124
109
0
05 Jul 2021
GNNAutoScale: Scalable and Expressive Graph Neural Networks via
  Historical Embeddings
GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings
Matthias Fey
J. E. Lenssen
F. Weichert
J. Leskovec
GNN
38
134
0
10 Jun 2021
Graph Neural Networks Inspired by Classical Iterative Algorithms
Graph Neural Networks Inspired by Classical Iterative Algorithms
Yongyi Yang
T. Liu
Yangkun Wang
Jinjing Zhou
Quan Gan
Zhewei Wei
Zheng Zhang
Zengfeng Huang
David Wipf
71
82
0
10 Mar 2021
Revisiting Graph Convolutional Network on Semi-Supervised Node
  Classification from an Optimization Perspective
Revisiting Graph Convolutional Network on Semi-Supervised Node Classification from an Optimization Perspective
Hongwei Zhang
Tijin Yan
Zenjun Xie
Yuanqing Xia
Yuan Zhang
GNN
65
24
0
24 Sep 2020
Towards Deeper Graph Neural Networks
Towards Deeper Graph Neural Networks
Meng Liu
Hongyang Gao
Shuiwang Ji
GNN
AI4CE
95
605
0
18 Jul 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs
Open Graph Benchmark: Datasets for Machine Learning on Graphs
Weihua Hu
Matthias Fey
Marinka Zitnik
Yuxiao Dong
Hongyu Ren
Bowen Liu
Michele Catasta
J. Leskovec
298
2,725
0
02 May 2020
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph
  Convolutional Networks
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
Wei-Lin Chiang
Xuanqing Liu
Si Si
Yang Li
Samy Bengio
Cho-Jui Hsieh
GNN
142
1,272
0
20 May 2019
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
232
7,638
0
01 Oct 2018
Relational inductive biases, deep learning, and graph networks
Relational inductive biases, deep learning, and graph networks
Peter W. Battaglia
Jessica B. Hamrick
V. Bapst
Alvaro Sanchez-Gonzalez
V. Zambaldi
...
Pushmeet Kohli
M. Botvinick
Oriol Vinyals
Yujia Li
Razvan Pascanu
AI4CE
NAI
739
3,119
0
04 Jun 2018
FastGCN: Fast Learning with Graph Convolutional Networks via Importance
  Sampling
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling
Jie Chen
Tengfei Ma
Cao Xiao
GNN
141
1,513
0
30 Jan 2018
Inductive Representation Learning on Large Graphs
Inductive Representation Learning on Large Graphs
William L. Hamilton
Z. Ying
J. Leskovec
472
15,218
0
07 Jun 2017
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNN
SSL
597
28,999
0
09 Sep 2016
1