Anime Link Prediction Using Improved Graph Convolutional Networks

Author:

Hmaidi Safae,Afoudi Yassine,Lazaar Mohamed,Yasser El Madani El Alami

Publisher

Springer Nature Switzerland

Reference15 articles.

1. Wu, Y., Lian, D., Xu, Y., Wu, L., Chen, E.: “Graph convolutional networks with Markov random field reasoning for social spammer detection. Proceed. AAAI Confer. Artif. Intell. 34(01), 1054–1061 (2020). https://doi.org/10.1609/AAAI.V34I01.5455

2. Sanchez-Gonzalez, A.: Graph networks as learnable physics engines for inference and control. proceedings.mlr.press (2018). http://proceedings.mlr.press/v80/sanchez-gonzalez18a.html. Accessed 31 May 2023

3. Battaglia, P., Pascanu, R., et al.: Interaction networks for learning about objects, relations and physics. proceedings.neurips.cc (2016). https://proceedings.neurips.cc/paper/2016/hash/3147da8ab4a0437c15ef51a5cc7f2dc4-Abstract.html. Accessed 31 May 2023

4. Fout, A., Byrd, J., et al.: Protein interface prediction using graph convolutional networks. proceedings.neurips.cc (2017). https://proceedings.neurips.cc/paper/2017/hash/f507783927f2ec2737ba40afbd17efb5-Abstract.html. Accessed 31 May 2023

5. Hamaguchi, T., Oiwa, H., Shimbo, M., Matsumoto, Y.: Knowledge transfer for out-of-knowledge-base entities: a graph neural network approach. IJCAI Int. Joint Confer. Artif. Intell. 4, 1802–1808 (2017)

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