On the Two Sides of Redundancy in Graph Neural Networks

Author:

Bause Franka,Moustafa Samir,Langguth Johannes,Gansterer Wilfried N.,Kriege Nils M.

Publisher

Springer Nature Switzerland

Reference40 articles.

1. Abboud, R., Ceylan, I.I., Grohe, M., Lukasiewicz, T.: The surprising power of graph neural networks with random node initialization. In: IJCAI (2021)

2. Abboud, R., Dimitrov, R., Ceylan, İ.İ.: Shortest path networks for graph property prediction. LoG (2022)

3. Abu-El-Haija, S., Perozzi, B., et al.: MixHop: higher-order graph convolutional architectures via sparsified neighborhood mixing. In: ICML (2019)

4. Aho, A.V., Hopcroft, J.E., Ullman, J.D.: The Design and Analysis of Computer Algorithms. Addison-Wesley (1974)

5. Alon, U., Yahav, E.: On the bottleneck of graph neural networks and its practical implications. In: ICLR (2021)

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