BioGNN: How Graph Neural Networks Can Solve Biological Problems-Reference-Cited by-同舟云学术

BioGNN: How Graph Neural Networks Can Solve Biological Problems

Published:2022-09-27 Issue: Volume: Page:211-231
ISSN:1868-4394
Container-title:Intelligent Systems Reference Library
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Author:

Bongini Pietro,Pancino Niccolò,Scarselli Franco,Bianchini Monica

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-11154-9_11

Reference80 articles.

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3. Wu, Z., Pan, S., Chen, F., Long, G., Zhang, C., Yu, P.S.: A comprehensive survey on graph neural networks. IEEE Trans. Neural Netw. Learn. Syst. (2020)

4. Gilmer, J., Schoenholz, S.S., Riley, P.F., Vinyals, O., Dahl, G.E.: Neural message passing for quantum chemistry. In: Proceedings of the 34th International Conference on Machine Learning, vol. 70, pp. 1263–1272 (2017)

5. Xu, K., Hu, W., Leskovec, J., Jegelka, S.: How powerful are graph neural networks? In: International Conference on Learning Representations (2018)

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