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As large-scale graphs become increasingly more prevalent, it poses significant computational challenges to process, extract and analyze large graph data.
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Daniel A Spielman and Shang-Hua Teng · 2004
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Leslie Hogben · 2005
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Multiscale wavelets on trees, graphs and high dimensional data: Theory and applications to semi supervised learning
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Daniel A Spielman and Nikhil Srivastava · 2011
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Spectral sparsification of graphs
Daniel A Spielman and Shang-Hua Teng · 2011
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Joshua Batson, Daniel A Spielman, and Nikhil Srivastava · 2012
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Michael Schlichtkrull, Thomas N Kipf, Peter Bloem, Rianne Van Den Berg, Ivan Titov, and Max Welling · 2018
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Graphvae: Towards generation of small graphs using variational autoencoders
Martin Simonovsky and Nikos Komodakis · 2018
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Crystal graph convolutional neural networks for an accurate and interpretable prediction of material properties
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Hierarchical graph representation learning with differentiable pooling
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Spectral sparsification and regret minimization beyond matrix multiplicative updates
Zeyuan Allen-Zhu, Zhenyu Liao, and Lorenzo Orecchia · 2015
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Convolutional networks on graphs for learning molecular fingerprints
David K Duvenaud, Dougal Maclaurin, Jorge Iparraguirre, Rafael Bombarell, Timothy Hirzel, Alán Aspuru-Guzik, and Ryan P Adams · 2015
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A multiscale pyramid transform for graph signals
David I Shuman, Mohammad Javad Faraji, and Pierre Vandergheynst · 2015
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Junhyun Lee, Inyeop Lee, and Jaewoo Kang · 2019
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Efficient graph generation with graph recurrent attention networks
Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, Will Hamilton, David K Duvenaud, Raquel Urtasun, and Richard Zemel · 2019
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Graph reduction with spectral and cut guarantees
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Tengfei Ma and Jie Chen · 2019
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Got: An optimal transport framework for graph comparison
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Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, and Viktor Prasanna · 2019
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Misc-gan: A multi-scale generative model for graphs
Dawei Zhou, Lecheng Zheng, Jiejun Xu, and Jingrui He · 2019
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The inverse eigenvalue problem of a graph, zero forcing, and related parameters
Shaun M Fallat, Leslie Hogben, Jephian C-H Lin, and Bryan L Shader · 2020
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A survey on graph kernels
Nils M Kriege, Fredrik D Johansson, and Christopher Morris · 2020
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Learning to simulate complex physics with graph networks
Alvaro Sanchez-Gonzalez, Jonathan Godwin, Tobias Pfaff, Rex Ying, Jure Leskovec, and Peter W Battaglia · 2020
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