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Graph matching refers to finding node correspondence between graphs, such that the corresponding node and edge's affinity can be maximized.
The hungarian method for the assignment problem
Harold W Kuhn · 1955
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The quadratic assignment problem
Eugene L. Lawler · 1963
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A relationship between arbitrary positive matrices and doubly stochastic matrices
Richard Sinkhorn · 1964
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Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography
Martin A. Fischler and Robert C. Bolles · 1981
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Computers and Intractability; A Guide to the Theory of NP-Completeness
Michael R. Garey and David S. Johnson · 1990
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Signature verification using a “siamese” time delay neural network
Jane Bromley, Isabelle Guyon, Yann LeCun, Eduard Säckinger, and Roopak Shah · 1994
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Iterative point matching for registration of free-form curves and surfaces
Zhengyou Zhang · 1994
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A graduated assignment algorithm for graph matching
Steven Gold and Anand Rangarajan · 1996
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Scale & affine invariant interest point detectors
Krystian Mikolajczyk and Cordelia Schmid · 2004
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A spectral technique for correspondence problems using pairwise constraints
Marius Leordeanu and Martial Hebert · 2005
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A survey for the quadratic assignment problem
Eliane Maria Loiola, Nair Maria Maia de Abreu, Paulo Oswaldo Boaventura-Netto, Peter Hahn, and Tania Querido · 2007
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Feature correspondence via graph matching: Models and global optimization
Lorenzo Torresani, Vladimir Kolmogorov, and Carsten Rother · 2008
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Probabilistic graph and hypergraph matching
Ron Zass and Amnon Shashua · 2008
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Poselets: Body part detectors trained using 3d human pose annotations
Lubomir Bourdev and Jitendra Malik · 2009
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Learning graph matching
Tiberio S. Caetano, Julian J. McAuley, Li Cheng, Quoc V. Le, and Alex J. Smola · 2009
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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The graph neural network model
Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini · 2009
Cited alongside, same era.
Efficient high order matching
Michael Chertok and Yosi Keller · 2010
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Reweighted random walks for graph matching
Minsu Cho, Jungmin Lee, and Kyoung Mu Lee · 2010
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The pascal visual object classes (voc) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
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Ranking via sinkhorn propagation
Ryan Prescott Adams and Richard S Zemel · 2011
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A tensor-based algorithm for high-order graph matching
Olivier Duchenne, Francis Bach, Kweon In-So, and Jean Ponce · 2011
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Line: Large-scale information network embedding
Jian Tang, Meng Qu, Mingzhe Wang, Ming Zhang, Jun Yan, and Qiaozhu Mei · 2015
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Discrete hyper-graph matching
Junchi Yan, Chao Zhang, Hongyuan Zha, Wei Liu, Xiaokang Yang, and Stephen M. Chu · 2015
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node2vec: Scalable feature learning for networks
Aditya Grover and Jure Leskovec · 2016
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Structural deep network embedding
Daixin Wang, Peng Cui, and Wenwu Zhu · 2016
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A short survey of recent advances in graph matching
Junchi Yan, Xu-Cheng Yin, Weiyao Lin, Cheng Deng, Hongyuan Zha, and Xiaokang Yang · 2016
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Semi-supervised classification with graph convolutional networks
Thomas N Kipf and Max Welling · 2017
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Hyper-graph matching via reweighted randomwalks
Jungmin Lee Lee, Minsu Cho, and Kyoung Mu Lee · 2011
Cited alongside, same era.
Semi-supervised learning and optimization for hypergraph matching
Marius Leordeanu, Andrei Zanfir, and Cristian Sminchisescu · 2011
Cited alongside, same era.
Automatic learning of edit costs based on interactive and adaptive graph recognition
Francesc Serratosa, Albert Solé-Ribalta, and Xavier Cortés · 2011
Cited alongside, same era.
Unsupervised learning for graph matching
Marius Leordeanu, Rahul Sukthankar, and Martial Hebert · 2012
Cited alongside, same era.
Graph matching techniques for computer vision
Mario Vento and Pasquale Foggia · 2012
Cited alongside, same era.
Learning graphs to match
Minsu Cho, Karteek Alahari, and Jean Ponce · 2013
Cited alongside, same era.
Sinkhorn networks: Using optimal transport techniques to learn permutations
Gonzalo Mena, David Belanger, Gonzalo Muñoz, and Jasper Snoek · 2017
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Deep sets
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Ruslan R Salakhutdinov, and Alexander J Smola · 2017
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Learning permutations with sinkhorn policy gradient
Patrick Emami and Sanjay Ranka · 2018
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Woute Kool and Max Welling · 2018
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Revised note on learning quadratic assignment with graph neural networks
Alex Nowak, Soledad Villar, Afonso S Bandeira, and Joan Bruna · 2018
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Giorgio Patrini, Marcello Carioni, Patrick Forre, Samarth Bhargav, Max Welling, Rianne van den Berg, Tim Genewein, and Frank Nielsen · 2018
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Visual permutation learning
Rodrigo Santa Cruz, Basura Fernando, Anoop Cherian, and Stephen Gould · 2018
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Deep learning of graph matching
Andrei Zanfir and Cristian Sminchisescu · 2018
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Graph neural networks: A review of methods and applications
Jie Zhou, Ganqu Cui, Zhengyan Zhang, Cheng Yang, Zhiyuan Liu, and Maosong Sun · 2018
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Coloring big graphs with alphagozero
Jiayi Huang, Mostofa Patwary, and Gregory Diamos · 2019
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