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Deep learning based approaches have been utilized to model and generate graphs subjected to different distributions recently.
Fuzzy cognitive maps
Bart Kosko et al · 1986
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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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Dialogue on reverse-engineering assessment and methods: the DREAM of high-throughput pathway inference
Gustavo Stolovitzky, DON Monroe, and Andrea Califano · 2007
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Sparse inverse covariance estimation with the graphical lasso
Jerome Friedman, Trevor Hastie, and Robert Tibshirani · 2008
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Generating realistic in silico gene networks for performance assessment of reverse engineering methods
Daniel Marbach, Thomas Schaffter, Claudio Mattiussi, and Dario Floreano · 2009
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DREAM4: Combining genetic and dynamic information to identify biological networks and dynamical models
Alex Greenfield, Aviv Madar, Harry Ostrer, and Richard Bonneau · 2010
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Dominating clasp of the financial sector revealed by partial correlation analysis of the stock market
Dror Y Kenett, Michele Tumminello, Asaf Madi, Gitit Gur-Gershgoren, Rosario N Mantegna, and Eshel Ben-Jacob · 2010
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Learning of fuzzy cognitive maps using density estimate
Wojciech Stach, Witold Pedrycz, and Lukasz A Kurgan · 2012
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Detecting causality in complex ecosystems
George Sugihara, Robert May, Hao Ye, Chih-hao Hsieh, Ethan Deyle, Michael Fogarty, and Stephan Munch · 2012
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Reasoning with neural tensor networks for knowledge base completion
Richard Socher, Danqi Chen, Christopher D Manning, and Andrew Ng · 2013
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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The HIM glocal metric and kernel for network comparison and classification
Giuseppe Jurman, Roberto Visintainer, Michele Filosi, Samantha Riccadonna, and Cesare Furlanello · 2015
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Gated graph sequence neural networks
Yujia Li, Daniel Tarlow, Marc Brockschmidt, and Richard Zemel · 2015
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A dynamic multiagent genetic algorithm for gene regulatory network reconstruction based on fuzzy cognitive maps
Jing Liu, Yaxiong Chi, and Chen Zhu · 2015
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Learning to compare image patches via convolutional neural networks
Sergey Zagoruyko and Nikos Komodakis · 2015
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Semi-supervised classification with graph convolutional networks
Thomas N Kipf and Max Welling · 2016
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Graphite: Iterative generative modeling of graphs
Aditya Grover, Aaron Zweig, and Stefano Ermon · 2018
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Xiaojie Guo, Lingfei Wu, and Liang Zhao · 2018
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Junction tree variational autoencoder for molecular graph generation
Wengong Jin, Regina Barzilay, and Tommi Jaakkola · 2018
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Simple recurrent units for highly parallelizable recurrence
Tao Lei, Yu Zhang, Sida I. Wang, Hui Dai, and Yoav Artzi · 2018
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Learning deep generative models of graphs
Yujia Li, Oriol Vinyals, Chris Dyer, Razvan Pascanu, and Peter Battaglia · 2018
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Variational graph auto-encoders
Thomas N Kipf and Max Welling · 2016
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Modeling time series similarity with siamese recurrent networks
Wenjie Pei, David MJ Tax, and Laurens van der Maaten · 2016
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Instance normalization: The missing ingredient for fast stylization
Dmitry Ulyanov, Andrea Vedaldi, and Victor Lempitsky · 2016
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Objective-reinforced generative adversarial networks (ORGAN) for sequence generation models
Gabriel Lima Guimaraes, Benjamin Sanchez-Lengeling, Carlos Outeiral, Pedro Luis Cunha Farias, and Alán Aspuru-Guzik · 2017
Cited alongside, same era.
NetGAN: Generating graphs via random walks
Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zügner, and Stephan Günnemann · 2018
Cited alongside, same era.
MolGAN: An implicit generative model for small molecular graphs
Nicola De Cao and Thomas Kipf · 2018
Cited alongside, same era.
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GraphVAE: Towards generation of small graphs using variational autoencoders
Martin Simonovsky and Nikos Komodakis · 2018
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GraphRNN: Generating realistic graphs with deep auto-regressive models
Jiaxuan You, Rex Ying, Xiang Ren, William L Hamilton, and Jure Leskovec · 2018
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SimGNN: A neural network approach to fast graph similarity computation
Yunsheng Bai, Hao Ding, Song Bian, Ting Chen, Yizhou Sun, and Wei Wang · 2019
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Labeled graph generative adversarial networks
Shuangfei Fan and Bert Huang · 2019
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Conditional structure generation through graph variational generative adversarial nets
Carl Yang, Peiye Zhuang, Wenhan Shi, Alan Luu, and Pan Li · 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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