MST-HGCN: a minimum spanning tree hyperbolic graph convolutional network

Author:

Liu YanxiORCID,Lang Bo,Quan Fengnan

Funder

State Key Laboratory of Software Development Environment

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Reference47 articles.

1. Kipf TN, Welling M (2017) Semi-supervised classification with graph convolutional networks. In: 5th International conference on learning representations, ICLR, Toulon, France, 24-26 April 2017, conference track proceedings

2. Chami I, Ying Z, Ré C, Leskovec J (2019) Hyperbolic graph convolutional neural networks. In: Wallach H, Larochelle H, Beygelzimer A, Dalché-buc F, Fox E, Garnett R (eds) Advances in neural information processing systems

3. Rong Y, Huang W, Xu T, Huang J (2019) Dropedge: towards deep graph convolutional networks on node classification. In: International conference on learning representations

4. Chen H, Xu Y, Huang F, Deng Z, Huang W, Wang S, He P, Li Z (2020) Label-aware graph convolutional networks. In: Proceedings of the 29th ACM international conference on information & knowledge management. ACM, pp 1977–1980. https://doi.org/10.1145/3340531.3412139

5. Corso G, Cavalleri L, Beaini D, Liò P, Veličković P (2020) Principal neighbourhood aggregation for graph nets. In: Advances in neural information processing systems, vol 33, pp 13260–13271

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