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Graph kernels have been successfully applied to many graph classification problems.
Williams, C.K., Seeger, M.: Using the Nyström Method to Speed Up Kernel Machines. In: NIPS. pp. 661–667 (2000)
2000
Earlier work this paper cites.
Horváth, T., Gärtner, T., Wrobel, S.: Cyclic Pattern Kernels for Predictive Graph Mining. In: KDD. pp. 158–167 (2004)
2004
Earlier work this paper cites.
Borgwardt, K.M., Kriegel, H.: Shortest-path kernels on graphs. In: ICDM. pp. 74–81 (2005)
2005
Earlier work this paper cites.
Blondel, V.D., Guillaume, J.L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. JSTAT 2008
2008
Earlier work this paper cites.
Shervashidze, N., Vishwanathan, S., Petri, T., Mehlhorn, K., Borgwardt, K.M.: Efficient graphlet kernels for large graph comparison. In: AISTATS. pp. 488–495 (2009)
2009
Earlier work this paper cites.
Vishwanathan, S.V.N., Schraudolph, N.N., Kondor, R., Borgwardt, K.M.: Graph Kernels. JMLR 11
2010
Earlier work this paper cites.
Shervashidze, N., Schweitzer, P., Van Leeuwen, E.J., Mehlhorn, K., Borgwardt, K.M.: Weisfeiler-Lehman Graph Kernels. JMLR 12
2011
Earlier work this paper cites.
Bruna, J., Zaremba, W., Szlam, A., LeCun, Y.: Spectral Networks and Locally connected networks on Graphs. In: ICLR (2014)
2014
Cited alongside, same era.
Johansson, F., Jethava, V., Dubhashi, D., Bhattacharyya, C.: Global graph kernels using geometric embeddings. In: ICML. pp. 694–702 (2014)
2014
Cited alongside, same era.
Yanardag, P., Vishwanathan, S.: A Structural Smoothing Framework For Robust Graph Comparison. In: NIPS. pp. 2125–2133 (2015)
2015
Cited alongside, same era.
Yanardag, P., Vishwanathan, S.: Deep Graph Kernels. In: KDD. pp. 1365–1374 (2015)
2015
Cited alongside, same era.
Defferrard, M., Bresson, X., Vandergheynst, P.: Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering. In: NIPS. pp. 3837–3845 (2016)
2016
Cited alongside, same era.
Niepert, M., Ahmed, M., Kutzkov, K.: Learning Convolutional Neural Networks for Graphs. In: ICML (2016)
2016
Later among the works it cites.
2016
Later among the works it cites.
Kipf, T.N., Welling, M.: Semi-Supervised Classification with Graph Convolutional Networks. In: ICLR (2017)
2017
Closest in time.
Nikolentzos, G., Meladianos, P., Vazirgiannis, M.: Matching Node Embeddings for Graph Similarity. In: AAAI. pp. 2429–2435 (2017)
2017
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2017
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Fortunato, S., Hric, D.: Community detection in networks: A user guide. Physics Reports 659
2016
Cited alongside, same era.
Kondor, R., Pan, H.: The Multiscale Laplacian Graph Kernel. In: NIPS. pp. 2982–2990 (2016)
2016
Cited alongside, same era.
Closest in time.