Fetching the paper…
Reading the bibliography…
Graph convolutional networks have made great progress in graph-based semi-supervised learning.
A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
Karypis, G.; and Kumar, V. 1998 · 1998
Earlier work this paper cites.
Unifying Graph Convolutional Neural Networks and Label Propagation
Hongwei, W.; and Jure, L. 2020 · 2002
Earlier work this paper cites.
Learning with local and global consistency
Zhou, D.; Bousquet, O.; Lal, T. N.; Weston, J.; and Schölkopf, B. 2004 · 2004
Earlier work this paper cites.
Semi-Supervised Learning with Graphs
Zhu, X.; Lafferty, J.; and Rosenfeld, R. 2005 · 2005
Earlier work this paper cites.
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
Belkin, M.; Niyogi, P.; and Sindhwani, V. 2006 · 2006
Earlier work this paper cites.
Collective Classification in Network Data
Sen, P.; Namata, G.; Bilgic, M.; Getoor, L.; Galligher, B.; and Eliassi-Rad, T. 2008 · 2008
Earlier work this paper cites.
Efficient graph-based semi-supervised learning of structured tagging models
Subramanya, A.; Petrov, S.; and Pereira, F. 2010 · 2010
Earlier work this paper cites.
Distilling the Knowledge in a Neural Network
Geoffrey, E. H.; Oriol, V.; and Jeffrey, D. 2015 · 2015
Earlier work this paper cites.
Revisiting Semi-Supervised Learning with Graph Embeddings
Yang, Z.; Cohen, W. W.; and Salakhutdinov, R. 2016 · 2016
Earlier work this paper cites.
Inductive Representation Learning on Large Graphs
Hamilton, W. L.; Ying, R.; and Leskovec, J. 2017 · 2017
Earlier work this paper cites.
Semi-supervised classification with graph convolutional networks
Kipf, T. N.; and Welling, M. 2017 · 2017
Earlier work this paper cites.
When Does Label Propagation Fail? A View from a Network Generative Model
Yamaguchi, Y.; and Hayashi, K. 2017 · 2017
Earlier work this paper cites.
Bridging collaborative filtering and semi-supervised learning: a neural approach for poi recommendation
Yang, C.; Bai, L.; Zhang, C.; Yuan, Q.; and Han, J. 2017 · 2017
Cited alongside, same era.
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling
Chen, J.; Ma, T.; and Xiao, C. 2018 · 2018
Cited alongside, same era.
Graph-based semi-supervised learning with genomic data integration using condition-responsive genes applied to phenotype classification
Doostparast Torshizi, A.; and Petzold, L. R. 2018 · 2018
Cited alongside, same era.
Deeper insights into graph convolutional networks for semi-supervised learning
Li, Q.; Han, Z.; and Wu, X.-M. 2018 · 2018
Cited alongside, same era.
Spatial and class structure regularized sparse representation graph for semi-supervised hyperspectral image classification
Shao, Y.; Sang, N.; Gao, C.; and Ma, L. 2018 · 2018
Cited alongside, same era.
Simplifying Graph Convolutional Networks
Wu, F.; Souza, A.; Zhang, T.; Fifty, C.; Yu, T.; and Weinberger, K. 2019 · 2019
Later among the works it cites.
Simple and deep graph convolutional networks
Chen, M.; Wei, Z.; Huang, Z.; Ding, B.; and Li, Y. 2020 · 2020
Later among the works it cites.
Graph Random Neural Networks for Semi-Supervised Learning on Graphs
Feng, W.; Zhang, J.; Dong, Y.; Han, Y.; Luan, H.; Xu, Q.; Yang, Q.; Kharlamov, E.; and Tang, J. 2020 · 2020
Later among the works it cites.
Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes
Ke, S.; Zhouchen, L.; and Zhanxing, Z. 2020 · 2020
Later among the works it cites.
Co-gcn for multi-view semi-supervised learning
Li, S.; Li, W.-T.; and Wang, W. 2020 · 2020
Later among the works it cites.
When Does Self-Supervision Help Graph Convolutional Networks?
You, Y.; Chen, T.; Wang, Z.; and Shen, Y. 2020 · 2020
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Graph Attention Networks
Veličković, P.; Cucurull, G.; Casanova, A.; Romero, A.; Liò, P.; and Bengio, Y. 2018 · 2018
Cited alongside, same era.
Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing
Abu-El-Haija, S.; Perozzi, B.; Kapoor, A.; Alipourfard, N.; Lerman, K.; Harutyunyan, H.; Ver Steeg, G.; and Galstyan, A. 2019 · 2019
Cited alongside, same era.
Predict then Propagate: Graph Neural Networks meet Personalized PageRank
Klicpera, J.; Bojchevski, A.; and Günnemann, S. 2019 · 2019
Cited alongside, same era.
Label efficient semi-supervised learning via graph filtering
Li, Q.; Wu, X.-M.; Liu, H.; Zhang, X.; and Guan, Z. 2019 · 2019
Cited alongside, same era.
Gmnn: Graph markov neural networks
Qu, M.; Bengio, Y.; and Tang, J. 2019 · 2019
Cited alongside, same era.
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
Rong, Y.; Huang, W.; Xu, T.; and Huang, J. 2019 · 2019
Cited alongside, same era.
Later among the works it cites.
Self-Distillation as Instance-Specific Label Smoothing
Zhang, Z.; and Sabuncu, M. 2020 · 2020
Later among the works it cites.
Adaptive Universal Generalized PageRank Graph Neural Network
Chien, E.; Peng, J.; Li, P.; and Milenkovic, O. 2021 · 2021
Closest in time.
Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning
Wan, S.; Pan, S.; Yang, J.; and Gong, C. 2021 · 2021
Closest in time.
Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework
Yang, C.; Liu, J.; and Shi, C. 2021 · 2021
Closest in time.
Graph U-Nets
Gao, H.; and Ji, S. 2019 · 2092
Closest in time.