2020

Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Mernyei, Péter, Cangea, Cătălina

Understand

We present Wiki-CS, a novel dataset derived from Wikipedia for benchmarking Graph Neural Networks.

The dataset consists of nodes corresponding to Computer Science articles, with edges based on hyperlinks and 10 classes representing different branches of the field.
We use the dataset to evaluate semi-supervised node classification and single-relation link prediction models.
Our experiments show that these methods perform well on a new domain, with structural properties different from earlier benchmarks.

GloVe: Global Vectors for Word Representation
Pennington, J., Socher, R., and Manning, C. D · 2014
Earlier work this paper cites.
Cleansing Wikipedia Categories using Centrality
Boldi, P. and Monti, C · 2016
Earlier work this paper cites.
Revisiting semi-supervised learning with graph embeddings
Original
Yang, Z., Cohen, W. W., and Salakhutdinov, R · 2016
Earlier work this paper cites.
Inductive representation learning on large graphs
Hamilton, W., Ying, Z., and Leskovec, J · 2017
Earlier work this paper cites.
Graph attention networks
Original
Veličković, P., Cucurull, G., Casanova, A., Romero, A., Lio, P., and Bengio, Y · 2017
Earlier work this paper cites.

Personalized Embedding Propagation: Combining Neural Networks on Graphs with Personalized PageRank
Original
Klicpera, J., Bojchevski, A., and Günnemann, S · 2018
Cited alongside, same era.
Pitfalls of graph neural network evaluation
Original
Shchur, O., Mumme, M., Bojchevski, A., and Günnemann, S · 2018
Cited alongside, same era.
Graph Star Net for Generalized Multi-Task Learning
Original
Haonan, L., Huang, S. H., Ye, T., and Xiuyan, G · 2019
Cited alongside, same era.
Understanding attention in graph neural networks
Original
Knyazev, B., Taylor, G. W., and Amer, M. R · 2019
Cited alongside, same era.
A Comprehensive Survey on Graph Neural Networks
Original
Wu, Z., Pan, S., Chen, F., Long, G., Zhang, C., and Yu, P. S · 2019
Cited alongside, same era.
Semi-Supervised Classification with Graph Convolutional Networks
Original
Kipf, T. N. and Welling, M
Cited in the paper.
Variational graph auto-encoders
Original
Kipf, T. N. and Welling, M
Cited in the paper.

Graphsaint: Graph sampling based inductive learning method
Original
Zeng, H., Zhou, H., Srivastava, A., Kannan, R., and Prasanna, V · 2019
Later among the works it cites.
Deep graph mapper: Seeing graphs through the neural lens
Original
Bodnar, C., Cangea, C., and Liò, P · 2020
Closest in time.
Benchmarking graph neural networks
Original
Dwivedi, V. P., Joshi, C. K., Laurent, T., Bengio, Y., and Bresson, X · 2020
Closest in time.
Open graph benchmark: Datasets for machine learning on graphs
Original
Hu, W., Fey, M., Zitnik, M., Dong, Y., Ren, H., Liu, B., Catasta, M., and Leskovec, J · 2020
Closest in time.

alphaXiv searches the wider corpus for related work and actual follow-ups.

alphaXiv is searching for related work…

Reading the bibliography…