Bibliography

BNO04

Albert-Laszlo Barabasi and Zoltan N Oltvai. Network biology: understanding the cell’s functional organization. Nature reviews. Genetics, 5:101–13, 03 2004. doi:10.1038/nrg1272.

BBS15

Anas Belahcen, Monica Bianchini, and Franco Scarselli. Web Spam Detection Using Transductive-Inductive Graph Neural Networks, pages 83–91. Springer International Publishing, Cham, 2015. URL: https://doi.org/10.1007/978-3-319-18164-6_9, doi:10.1007/978-3-319-18164-6_9.

BM13

Monica Bianchini and Marco Maggini. Supervised neural network models for processing graphs. In Handbook on Neural Information Processing, volume 49 of Intelligent Systems Reference Library, pages 67–96. Springer, 2013.

New10

Mark Newman. Networks: An Introduction. Oxford University Press, Inc., New York, NY, USA, 2010. ISBN 0199206651, 9780199206650.

RTD+18

Alberto Rossi, Matteo Tiezzi, Giovanna Maria Dimitri, Monica Bianchini, Marco Maggini, and Franco Scarselli. Inductive-transductive learning with graph neural networks. In ANNPR. 2018.

SGT+09a

Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini. Computational capabilities of graph neural networks. IEEE Transactions on Neural Networks, 20:81–102, 2009.

SGT+09b

Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini. The graph neural network model. IEEE Transactions on Neural Networks, 20:61–80, 2009.

Spo03

Olaf Sporns. Graph Theory Methods for the Analysis of Neural Connectivity Patterns, pages 171–185. Springer US, Boston, MA, 2003. URL: https://doi.org/10.1007/978-1-4615-1079-6_12, doi:10.1007/978-1-4615-1079-6_12.