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In this paper, we present GGSD, a novel graph generative model based on 1) the spectral decomposition of the graph Laplacian matrix and 2) a diffusion process.
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Spectral graph theory , volume 92
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Statistical mechanics of complex networks
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Distinguishing enzyme structures from non-enzymes without alignments
Paul D Dobson and Andrew J Doig · 2003
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Spectral embedding of graphs
Bin Luo, Richard C Wilson, and Edwin R Hancock · 2003
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Christos Faloutsos · 2008
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Kronecker graphs: an approach to modeling networks
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Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Stable and informative spectral signatures for graph matching
Nan Hu, Raif M Rustamov, and Leonidas Guibas · 2014
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Tiago P. Peixoto · 2014
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Quantum chemistry structures and properties of 134 kilo molecules
Raghunathan Ramakrishnan, Pavlo O Dral, Matthias Rupp, and O Anatole Von Lilienfeld · 2014
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A quantum jensen–shannon graph kernel for unattributed graphs
Lu Bai, Luca Rossi, Andrea Torsello, and Edwin R Hancock · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Luca Cosmo, Emanuele Rodola, Jonathan Masci, Andrea Torsello, and Michael M Bronstein · 2016
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Emanuele Rodolà, Luca Cosmo, Michael M Bronstein, Andrea Torsello, and Daniel Cremers · 2017
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin · 2017
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Molgan: An implicit generative model for small molecular graphs
Permutation invariant graph generation via score-based generative modeling
Chenhao Niu, Yang Song, Jiaming Song, Shengjia Zhao, Aditya Grover, and Stefano Ermon · 2020
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Nevae: A deep generative model for molecular graphs
Bidisha Samanta, Abir De, Gourhari Jana, Vicenç Gómez, Pratim Chattaraj, Niloy Ganguly, and Manuel Gomez-Rodriguez · 2020
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Chence Shi, Minkai Xu, Zhaocheng Zhu, Weinan Zhang, Ming Zhang, and Jian Tang · 2020
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Graphdf: A discrete flow model for molecular graph generation
Youzhi Luo, Keqiang Yan, and Shuiwang Ji · 2021
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Spectral shape recovery and analysis via data-driven connections
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Nicola De Cao and Thomas Kipf · 2018
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Automatic chemical design using a data-driven continuous representation of molecules
Rafael Gómez-Bombarelli, Jennifer N Wei, David Duvenaud, José Miguel Hernández-Lobato, Benjamín Sánchez-Lengeling, Dennis Sheberla, Jorge Aguilera-Iparraguirre, Timothy D Hirzel, Ryan P Adams, and Alán Aspuru-Guzik · 2018
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Martin Simonovsky and Nikos Komodakis · 2018
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Random graph modeling: A survey of the concepts
Mikhail Drobyshevskiy and Denis Turdakov · 2019
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Graphite: Iterative generative modeling of graphs
Aditya Grover, Aaron Zweig, and Stefano Ermon · 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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Universal spectral adversarial attacks for deformable shapes
Arianna Rampini, Franco Pestarini, Luca Cosmo, Simone Melzi, and Emanuele Rodola · 2021
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3d shape analysis through a quantum lens: the average mixing kernel signature
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A systematic survey on deep generative models for graph generation
Xiaojie Guo and Liang Zhao · 2022
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Diffusion models for graphs benefit from discrete state spaces
Kilian Konstantin Haefeli, Karolis Martinkus, Nathanaël Perraudin, and Roger Wattenhofer · 2022
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Graphgdp: Generative diffusion processes for permutation invariant graph generation
Han Huang, Leilei Sun, Bowen Du, Yanjie Fu, and Weifeng Lv · 2022
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Score-based generative modeling of graphs via the system of stochastic differential equations
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Graphusion: Latent diffusion for graph generation
Ling Yang, Zhilin Huang, Zhilong Zhang, Zhongyi Liu, Shenda Hong, Wentao Zhang, Wenming Yang, Bin Cui, and Luxia Zhang · 2024
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