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Graph neural networks (GNNs) have achieved great success in many graph-based tasks.
Long short-term memory
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Birds of a feather: Homophily in social networks
Miller McPherson, Lynn Smith-Lovin, and James M Cook · 2001
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Community structure in social and biological networks
Michelle Girvan and Mark EJ Newman · 2002
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Statistical mechanics of complex networks
Réka Albert and Albert-László Barabási · 2002
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Bochner’s method for cell complexes and combinatorial ricci curvature
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Communities in networks
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Yann Ollivier · 2009
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Combinatorial ricci curvature and laplacians for image processing
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A survey of ricci curvature for metric spaces and markov chains
Yann Ollivier et al · 2010
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Ricci curvature of graphs
Yong Lin, Linyuan Lu, and Shing-Tung Yau · 2011
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Spectral statistics of erdős–rényi graphs i: Local semicircle law
László Erdős, Antti Knowles, Horng-Tzer Yau, Jun Yin, et al · 2013
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Spectral networks and deep locally connected networks on graphs
Joan Bruna, Wojciech Zaremba, Arthur Szlam, and Yann LeCun · 2014
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Learning phrase representations using rnn encoder-decoder for statistical machine translation
Kyunghyun Cho, B van Merrienboer, Caglar Gulcehre, F Bougares, H Schwenk, and Yoshua Bengio · 2014
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Wireless network capacity versus ollivier-ricci curvature under heat-diffusion (hd) protocol
Chi Wang, Edmond Jonckheere, and Reza Banirazi · 2014
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Convolutional networks on graphs for learning molecular fingerprints
David Duvenaud, Dougal Maclaurin, Jorge Aguilera-Iparraguirre, Rafael Gómez-Bombarelli, Timothy Hirzel, Alán Aspuru-Guzik, and Ryan P Adams · 2015
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Deep convolutional networks on graph-structured data
Mikael Henaff, Joan Bruna, and Yann LeCun · 2015
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Gated graph sequence neural networks
Yujia Li, Daniel Tarlow, Marc Brockschmidt, and Richard Zemel · 2015
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Improved semantic representations from tree-structured long short-term memory networks
Kai Sheng Tai, Richard Socher, and Christopher D Manning · 2015
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Ricci curvature of the internet topology
Chien-Chun Ni, Yu-Yao Lin, Jie Gao, Xianfeng David Gu, and Emil Saucan · 2015
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node2vec: Scalable feature learning for networks
Aditya Grover and Jure Leskovec · 2016
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Semi-supervised classification with graph convolutional networks
Thomas N Kipf and Max Welling · 2016
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Convolutional neural networks on graphs with fast localized spectral filtering
Michaël Defferrard, Xavier Bresson, and Pierre Vandergheynst · 2016
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Ricci curvature: An economic indicator for market fragility and systemic risk
Romeil S Sandhu, Tryphon T Georgiou, and Allen R Tannenbaum · 2016
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Revisiting semi-supervised learning with graph embeddings
Zhilin Yang, William Cohen, and Ruslan Salakhudinov · 2016
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Protein interface prediction using graph convolutional networks
Graph transformation policy network for chemical reaction prediction
Kien Do, Truyen Tran, and Svetha Venkatesh · 2019
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Batch virtual adversarial training for graph convolutional networks
Zhijie Deng, Yinpeng Dong, and Jun Zhu · 2019
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Simplifying graph convolutional networks
Felix Wu, Amauri Souza, Tianyi Zhang, Christopher Fifty, Tao Yu, and Kilian Weinberger · 2019
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Curvature graph network
Ze Ye, Kin Sum Liu, Tengfei Ma, Jie Gao, and Chao Chen · 2019
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Hyperbolic graph convolutional neural networks
Ines Chami, Rex Ying, Christopher Ré, and Jure Leskovec · 2019
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Deepsphere: towards an equivariant graph-based spherical cnn
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Alex Fout, Jonathon Byrd, Basir Shariat, and Asa Ben-Hur · 2017
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Inductive representation learning on large graphs
William L Hamilton, Rex Ying, and Jure Leskovec · 2017
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Topology adaptive graph convolutional networks
Jian Du, Shanghang Zhang, Guanhang Wu, José MF Moura, and Soummya Kar · 2017
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Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio · 2017
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Geometric deep learning on graphs and manifolds using mixture model cnns
Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodola, Jan Svoboda, and Michael M Bronstein · 2017
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Characterizing complex networks with forman-ricci curvature and associated geometric flows
Melanie Weber, Emil Saucan, and Jürgen Jost · 2017
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Community detection and stochastic block models: recent developments
Emmanuel Abbe · 2017
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Michaël Defferrard, Nathanaël Perraudin, Tomasz Kacprzak, and Raphael Sgier · 2019
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Community detection on networks with ricci flow
Chien-Chun Ni, Yu-Yao Lin, Feng Luo, and Jie Gao · 2019
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Ollivier-ricci curvature-based method to community detection in complex networks
Jayson Sia, Edmond Jonckheere, and Paul Bogdan · 2019
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Fast graph representation learning with PyTorch Geometric
Matthias Fey and Jan E. Lenssen · 2019
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Dropedge: Towards deep graph convolutional networks on node classification
Yu Rong, Wenbing Huang, Tingyang Xu, and Junzhou Huang · 2019
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Measuring and relieving the over-smoothing problem for graph neural networks from the topological view
Deli Chen, Yankai Lin, Wei Li, Peng Li, Jie Zhou, and Xu Sun · 2020
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A comprehensive survey on graph neural networks
Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, and S Yu Philip · 2020
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Constant curvature graph convolutional networks
Gregor Bachmann, Gary Bécigneul, and Octavian Ganea · 2020
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When does self-supervision help graph convolutional networks?
Yuning You, Tianlong Chen, Zhangyang Wang, and Yang Shen · 2020
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Self-supervised learning on graphs: Deep insights and new direction
Wei Jin, Tyler Derr, Haochen Liu, Yiqi Wang, Suhang Wang, Zitao Liu, and Jiliang Tang · 2020
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Gcc: Graph contrastive coding for graph neural network pre-training
Jiezhong Qiu, Qibin Chen, Yuxiao Dong, Jing Zhang, Hongxia Yang, Ming Ding, Kuansan Wang, and Jie Tang · 2020
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Graph contrastive learning with augmentations
Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, and Yang Shen · 2020
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Wiki-cs: A wikipedia-based benchmark for graph neural networks
Péter Mernyei and Cătălina Cangea · 2020
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Graph Information Vanishing Phenomenon inImplicit Graph Neural Networks
Haifeng Li, Jun Cao, Jiawei Zhu, Qing Zhu, and Guohua Wu · 2021
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