Fetching the paper…
Reading the bibliography…
Message Passing Neural Networks (MPNNs) have emerged as the {\em de facto} standard in graph representation learning.
Provably Powerful Graph Networks
Haggai Maron, Heli Ben-Hamu, Hadar Serviansky, and Yaron Lipman · 1905
Earlier work this paper cites.
A new status index derived from sociometric analysis
Leo Katz · 1953
Earlier work this paper cites.
Extensions of Lipschitz maps into a Hilbert space
William Johnson and Joram Lindenstrauss · 1984
Earlier work this paper cites.
Introduction to Modern Information Retrieval
Gerard Salton and Michael J. McGill · 1986
Earlier work this paper cites.
Orthogonal dimension and tolerance
Paul C Kainen · 1992
Earlier work this paper cites.
Quasiorthogonal dimension of euclidean spaces
Paul C. Kainen and Vĕra Kůrková · 1993
Earlier work this paper cites.
The Anatomy of a Large-Scale Hypertextual Web Search Engine
Sergey Brin and Lawrence Page · 1998
Earlier work this paper cites.
Collective dynamics of ‘small-world’ networks
Duncan J. Watts and Steven H. Strogatz · 1998
Earlier work this paper cites.
Emergence of Scaling in Random Networks
Albert-László Barabási and Réka Albert · 1999
Earlier work this paper cites.
Can Graph Neural Networks Count Substructures?
Zhengdao Chen, Lei Chen, Soledad Villar, and Joan Bruna · 2002
Earlier work this paper cites.
Random Features Strengthen Graph Neural Networks, 2021
Ryoma Sato, Makoto Yamada, and Hisashi Kashima · 2002
Earlier work this paper cites.
Comparative assessment of large-scale data sets of protein–protein interactions
Christian Von Mering, Roland Krause, Berend Snel, Michael Cornell, Stephen G Oliver, Stanley Fields, and Peer Bork · 2002
Earlier work this paper cites.
Measuring ISP topologies with Rocketfuel
Neil Spring, Ratul Mahajan, and David Wetherall · 2002
Earlier work this paper cites.
The link prediction problem for social networks
David Liben-Nowell and Jon Kleinberg · 2003
Earlier work this paper cites.
Friends and neighbors on the Web
Lada A. Adamic and Eytan Adar · 2003
Earlier work this paper cites.
Open Graph Benchmark: Datasets for Machine Learning on Graphs
Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, and Jure Leskovec · 2005
Earlier work this paper cites.
Mapping the US political blogosphere: Are conservative bloggers more prominent?
Robert Ackland and others · 2005
Earlier work this paper cites.
Pajek datasets website, 2006
Vladimir Batagelj and Andrej Mrvar · 2006
Earlier work this paper cites.
Finding community structure in networks using the eigenvectors of matrices
Mark EJ Newman · 2006
Cited alongside, same era.
Matrix factorization techniques for recommender systems
Yehuda Koren, Robert Bell, and Chris Volinsky · 2009
Cited alongside, same era.
Predicting missing links via local information
Tao Zhou, Linyuan Lü, and Yi-Cheng Zhang · 2009
Cited alongside, same era.
The Surprising Power of Graph Neural Networks with Random Node Initialization, 2021
Ralph Abboud, Ismail Ilkan Ceylan, Martin Grohe, and Thomas Lukasiewicz · 2010
Cited alongside, same era.
Variational Graph Auto-Encoders, 2016
Thomas N. Kipf and Max Welling · 2016
Cited alongside, same era.
Semi-Supervised Classification with Graph Convolutional Networks
Thomas N. Kipf and Max Welling · 2017
Neural bellman-ford networks: A general graph neural network framework for link prediction
Zhaocheng Zhu, Zuobai Zhang, Louis-Pascal Xhonneux, and Jian Tang · 2021
Later among the works it cites.
Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning
Muhan Zhang, Pan Li, Yinglong Xia, Kai Wang, and Long Jin · 2021
Later among the works it cites.
Neo-GNNs: Neighborhood Overlap-aware Graph Neural Networks for Link Prediction
Seongjun Yun, Seoyoon Kim, Junhyun Lee, Jaewoo Kang, and Hyunwoo J. Kim · 2021
Later among the works it cites.
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks, November 2021
Christopher Morris, Martin Ritzert, Matthias Fey, William L. Hamilton, Jan Eric Lenssen, Gaurav Rattan, and Martin Grohe · 2021
Later among the works it cites.
Nested Graph Neural Networks, 2021
Muhan Zhang and Pan Li · 2021
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Neural Message Passing for Quantum Chemistry
Justin Gilmer, Samuel S. Schoenholz, Patrick F. Riley, Oriol Vinyals, and George E. Dahl · 2017
Cited alongside, same era.
Inductive Representation Learning on Large Graphs
William L. Hamilton, Rex Ying, and Jure Leskovec · 2018
Cited alongside, same era.
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio · 2018
Cited alongside, same era.
How Powerful are Graph Neural Networks?
Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka · 2018
Cited alongside, same era.
Link Prediction Based on Graph Neural Networks
Muhan Zhang and Yixin Chen · 2018
Cited alongside, same era.
Beyond link prediction: Predicting hyperlinks in adjacency space
Muhan Zhang, Zhicheng Cui, Shali Jiang, and Yixin Chen · 2018
Cited alongside, same era.
Later among the works it cites.
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks, November 2021
Pál András Papp, Karolis Martinkus, Lukas Faber, and Roger Wattenhofer · 2021
Later among the works it cites.
Graph Neural Networks for Link Prediction with Subgraph Sketching
Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Yannick Hammerla, Michael M. Bronstein, and Max Hansmire · 2022
Later among the works it cites.
Revisiting Embeddings for Graph Neural Networks
Skye Purchase, Yiren Zhao, and Robert D. Mullins · 2022
Later among the works it cites.
Shortest Path Networks for Graph Property Prediction
Ralph Abboud, Radoslav Dimitrov, and Ismail Ilkan Ceylan · 2022
Later among the works it cites.
How Powerful are K-hop Message Passing Graph Neural Networks
Jiarui Feng, Yixin Chen, Fuhai Li, Anindya Sarkar, and Muhan Zhang · 2022
Later among the works it cites.
FakeEdge: Alleviate Dataset Shift in Link Prediction
Kaiwen Dong, Yijun Tian, Zhichun Guo, Yang Yang, and Nitesh Chawla · 2022
Later among the works it cites.
Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning
Haoteng Yin, Muhan Zhang, Yanbang Wang, Jianguo Wang, and Pan Li · 2022
Later among the works it cites.
Refined Edge Usage of Graph Neural Networks for Edge Prediction
Jiarui Jin, Yangkun Wang, Weinan Zhang, Quan Gan, Xiang Song, Yong Yu, Zheng Zhang, and David Wipf · 2022
Later among the works it cites.
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries, June 2022
Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, and Haggai Maron · 2022
Later among the works it cites.
DotHash: Estimating Set Similarity Metrics for Link Prediction and Document Deduplication, May 2023
Igor Nunes, Mike Heddes, Pere Vergés, Danny Abraham, Alexander Veidenbaum, Alexandru Nicolau, and Tony Givargis · 2023
Closest in time.
Neural Common Neighbor with Completion for Link Prediction, February 2023
Xiyuan Wang, Haotong Yang, and Muhan Zhang · 2023
Closest in time.
Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, and Dawei Yin · 2023
Closest in time.