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We propose NetGAN - the first implicit generative model for graphs able to mimic real-world networks.
The asymptotic number of labeled graphs with given degree sequences
Bender, E. A. and Canfield, E. R · 1978
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An exponential family of probability distributions for directed graphs
Holland, P. W. and Leinhardt, S · 1981
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A critical point for random graphs with a given degree sequence
Molloy, M. and Reed, B · 1995
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Long short-term memory
Hochreiter, S. and Schmidhuber, J · 1997
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Emergence of scaling in random networks
Barabási, A.-L. and Albert, R · 1999
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Automating the construction of internet portals with machine learning
McCallum, A. K., Nigam, K., Rennie, J., and Seymore, K · 2000
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Friends and neighbors on the web
Adamic, L. A. and Adar, E · 2003
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The political blogosphere and the 2004 US election: divided they blog
Adamic, L. A. and Glance, N · 2005
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Graph mining: Laws, generators, and algorithms
Chakrabarti, D. and Faloutsos, C · 2006
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Multimedia retrieval
Blanken, H. M., de Vries, A. P., Blok, H. E., and Feng, L · 2007
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Collective classification in network data
Sen, P., Namata, G., Bilgic, M., Getoor, L., Galligher, B., and Eliassi-Rad, T · 2008
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A survey of statistical network models
Goldenberg, A., Zheng, A. X., Fienberg, S. E., Airoldi, E. M., et al · 2010
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Stochastic blockmodels and community structure in networks
Karrer, B. and Newman, M. E · 2011
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Modeling social networks with node attributes using the multiplicative attribute graph model
Kim, M. and Leskovec, J · 2011
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Community structure and scale-free collections of Erdős-Rényi graphs
Seshadhri, C., Kolda, T. G., and Pinar, A · 2012
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Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y · 2014
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Adam: A method for stochastic optimization
Kingma, D. and Ba, J · 2014
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Deepwalk: Online learning of social representations
Perozzi, B., Al-Rfou, R., and Skiena, S · 2014
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NIPS 2016 tutorial: Generative adversarial networks
Goodfellow, I · 2016
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node2vec: Scalable feature learning for networks
Grover, A. and Leskovec, J · 2016
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Structural diversity and homophily: A study across more than one hundred big networks
Dong, Y., Johnson, R. A., Xu, J., and Chawla, N. V · 2017
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Improved training of Wasserstein GANs
Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., and Courville, A · 2017
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ERGM: Fit, Simulate and Diagnose Exponential-Family Models for Networks
Handcock, M. S., Hunter, D. R., Butts, C. T., Goodreau, S. M., Krivitsky, P. N., and Morris, M · 2017
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Boundary-seeking generative adversarial networks
Hjelm, R. D., Jacob, A. P., Che, T., Cho, K., and Bengio, Y · 2017
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Progressive growing of gans for improved quality, stability, and variation
Karras, T., Aila, T., Laine, S., and Lehtinen, J · 2017
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Jang, E., Gu, S., and Poole, B · 2016
Cited alongside, same era.
Variational graph auto-encoders
Kipf, T. N. and Welling, M · 2016
Cited alongside, same era.
GANs for sequences of discrete elements with the Gumbel-softmax distribution
Kusner, M. J. and Hernández-Lobato, J. M · 2016
Cited alongside, same era.
Tri-party deep network representation
Pan, S., Wu, J., Zhu, X., Zhang, C., and Wang, Y · 2016
Cited alongside, same era.
Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling
Wu, J., Zhang, C., Xue, T., Freeman, B., and Tenenbaum, J · 2016
Cited alongside, same era.
Arjovsky, M., Chintala, S., and Bottou, L · 2017
Cited alongside, same era.
Began: Boundary equilibrium generative adversarial networks
Berthelot, D., Schumm, T., and Metz, L · 2017
Cited alongside, same era.
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Adversarial learning for neural dialogue generation
Li, J., Monroe, W., Shi, T., Ritter, A., and Jurafsky, D · 2017
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Recurrent topic-transition GAN for visual paragraph generation
Liang, X., Hu, Z., Zhang, H., Gan, C., and Xing, E. P · 2017
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Can GAN learn topological features of a graph?
Liu, W., Chen, P.-Y., Cooper, H., Oh, M. H., Yeung, S., and Suzumura, T · 2017
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Learning social graph topologies using generative adversarial neural networks
Tavakoli, S., Hajibagheri, A., and Sukthankar, G · 2017
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GraphGAN: Graph representation learning with generative adversarial nets
Wang, H., Wang, J., Wang, J., Zhao, M., Zhang, W., Zhang, F., Xie, X., and Guo, M · 2017
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SeqGAN: Sequence generative adversarial nets with policy gradient
Yu, L., Zhang, W., Wang, J., and Yu, Y · 2017
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Bayesian robust attributed graph clustering: Joint learning of partial anomalies and group structure
Bojchevski, A. and Günnemann, S · 2018
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Deep gaussian embedding of graphs: Unsupervised inductive learning via ranking
Bojchevski, A. and Günnemann, S · 2018
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Broido, A. D. and Clauset, A · 2018
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