ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2012.01380
  4. Cited By
v1v2v3 (latest)

Deep Graph Neural Networks with Shallow Subgraph Samplers

2 December 2020
Hanqing Zeng
Muhan Zhang
Yinglong Xia
Ajitesh Srivastava
Andrey Malevich
Rajgopal Kannan
Viktor Prasanna
Long Jin
Ren Chen
    GNN
ArXiv (abs)PDFHTML

Papers citing "Deep Graph Neural Networks with Shallow Subgraph Samplers"

16 / 16 papers shown
Title
A Simple and Scalable Graph Neural Network for Large Directed Graphs
A Simple and Scalable Graph Neural Network for Large Directed Graphs
Seiji Maekawa
Yuya Sasaki
Makoto Onizuka
GNN
217
1
0
14 Jun 2023
Efficiently Forgetting What You Have Learned in Graph Representation
  Learning via Projection
Efficiently Forgetting What You Have Learned in Graph Representation Learning via ProjectionInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Weilin Cong
Mehrdad Mahdavi
MU
86
23
0
17 Feb 2023
From Local to Global: Spectral-Inspired Graph Neural Networks
From Local to Global: Spectral-Inspired Graph Neural Networks
Ningyuan Huang
Soledad Villar
Carey E. Priebe
Da Zheng
Cheng-Fu Huang
Lin F. Yang
Vladimir Braverman
301
16
0
24 Sep 2022
GNN Transformation Framework for Improving Efficiency and Scalability
GNN Transformation Framework for Improving Efficiency and Scalability
Seiji Maekawa
Yuya Sasaki
G. Fletcher
Makoto Onizuka
GNN
120
2
0
25 Jul 2022
Beyond Real-world Benchmark Datasets: An Empirical Study of Node
  Classification with GNNs
Beyond Real-world Benchmark Datasets: An Empirical Study of Node Classification with GNNsNeural Information Processing Systems (NeurIPS), 2022
Seiji Maekawa
Koki Noda
Yuya Sasaki
Makoto Onizuka
324
30
0
18 Jun 2022
Transformer for Graphs: An Overview from Architecture Perspective
Transformer for Graphs: An Overview from Architecture Perspective
Erxue Min
Runfa Chen
Yatao Bian
Qifeng Bai
Kangfei Zhao
Wenbing Huang
P. Zhao
Junzhou Huang
Sophia Ananiadou
Yu Rong
224
184
0
17 Feb 2022
RETE: Retrieval-Enhanced Temporal Event Forecasting on Unified Query
  Product Evolutionary Graph
RETE: Retrieval-Enhanced Temporal Event Forecasting on Unified Query Product Evolutionary GraphThe Web Conference (WWW), 2022
Ruijie Wang
Zheng Li
Danqing Zhang
Qingyu Yin
Tong Zhao
Bing Yin
Tarek Abdelzaher
AI4TS
132
26
0
12 Feb 2022
GREED: A Neural Framework for Learning Graph Distance Functions
GREED: A Neural Framework for Learning Graph Distance FunctionsNeural Information Processing Systems (NeurIPS), 2021
Rishab Ranjan
Siddharth Grover
Sourav Medya
Venkatesan T. Chakaravarthy
Yogish Sabharwal
Jignesh M. Patel
GNN
211
55
0
24 Dec 2021
Network In Graph Neural Network
Network In Graph Neural Network
Xiang Song
Runjie Ma
Jiahang Li
Muhan Zhang
David Wipf
GNN
94
14
0
23 Nov 2021
Nested Graph Neural Networks
Nested Graph Neural NetworksNeural Information Processing Systems (NeurIPS), 2021
Muhan Zhang
Pan Li
234
194
0
25 Oct 2021
Tree Decomposed Graph Neural Network
Tree Decomposed Graph Neural NetworkInternational Conference on Information and Knowledge Management (CIKM), 2021
Yu Wang
Hanyu Wang
154
79
0
25 Aug 2021
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive
  Benchmark Study
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark StudyIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
Tianlong Chen
Kaixiong Zhou
Keyu Duan
Wenqing Zheng
Peihao Wang
Helen Zhou
Zinan Lin
AAMLGNN
133
73
0
24 Aug 2021
Evaluating Deep Graph Neural Networks
Evaluating Deep Graph Neural Networks
Wentao Zhang
Zeang Sheng
Yuezihan Jiang
Yikuan Xia
Jun Gao
Zhi-Xin Yang
Tengjiao Wang
GNNAI4CE
139
33
0
02 Aug 2021
GNNAutoScale: Scalable and Expressive Graph Neural Networks via
  Historical Embeddings
GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical EmbeddingsInternational Conference on Machine Learning (ICML), 2021
Matthias Fey
J. E. Lenssen
F. Weichert
J. Leskovec
GNN
158
144
0
10 Jun 2021
Towards Deepening Graph Neural Networks: A GNTK-based Optimization
  Perspective
Towards Deepening Graph Neural Networks: A GNTK-based Optimization PerspectiveInternational Conference on Learning Representations (ICLR), 2021
Wei Huang
Yayong Li
Weitao Du
Jie Yin
R. Xu
Ling-Hao Chen
Miao Zhang
163
19
0
03 Mar 2021
DeeperGCN: All You Need to Train Deeper GCNs
DeeperGCN: All You Need to Train Deeper GCNs
Guohao Li
Chenxin Xiong
Ali K. Thabet
Guohao Li
GNN
526
483
0
13 Jun 2020
1