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Recent advancements in graph representation learning have led to the emergence of condensed encodings that capture the main properties of a graph.
Clique pooling for graph classification
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Principal component analysis
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The PageRank Axioms
Altman, A · 2005
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PageRank as a Function of the Damping Factor
Boldi, P., Santini, M., and Vigna, S · 2005
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Topological Methods for the Analysis of High Dimensional Data Sets and 3D Object Recognition, 2007
Singh, G., Memoli, F., and Carlsson, G · 2007
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Persistent Homology—a Survey
Edelsbrunner, H. and Harer, J · 2008
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Exploring Network Structure, Dynamics, and Function using NetworkX
Hagberg, A., Swart, P., and S Chult, D · 2008
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The Graph Neural Network Model
Scarselli, F., Gori, M., Tsoi, A. C., Hagenbuchner, M., and Monfardini, G · 2008
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Collective Classification in Network Data
Sen, P., Namata, G., Bilgic, M., Getoor, L., Galligher, B., and Eliassi-Rad, T · 2008
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Visualizing Data using t-SNE
van der Maaten, L. and Hinton, G · 2008
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Gephi: An Open Source Software for Exploring and Manipulating Networks, 2009
Bastian, M., Heymann, S., and Jacomy, M · 2009
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NodeXL: a free and open network overview, discovery and exploration add-in for Excel 2007/2010
Smith, M., Milic-Frayling, N., Shneiderman, B., Mendes Rodrigues, E., Leskovec, J., and Dunne, C · 2010
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Motif Simplification: Improving Network Visualization Readability with Fan, Connector, and Clique Glyphs
Dunne, C. and Shneiderman, B · 2013
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Edge Compression Techniques for Visualization of Dense Directed Graphs
Dwyer, T., Henry Riche, N., Marriott, K., and Mears, C · 2013
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Statistical Analysis and Parameter Selection for Mapper
Carriere, M., Michel, B., and Oudot, S · 2018
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A look at the topology of convolutional neural networks
Gabrielsson, R. B. and Carlsson, G. E · 2018
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Veličković, P., Fedus, W., Hamilton, W. L., Liò, P., Bengio, Y., and Hjelm, R. D · 2018
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Hierarchical Graph Representation Learning with Differentiable Pooling
Ying, Z., You, J., Morris, C., Ren, X., Hamilton, W., and Leskovec, J · 2018
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Mincut Pooling in Graph Neural Networks
Bianchi, F. M., Grattarola, D., and Alippi, C · 2019
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Kingma, D. P. and Ba, J · 2014
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Benchmark Data Sets for Graph Kernels, 2016
Kersting, K., Kriege, N. M., Morris, C., Mutzel, P., and Neumann, M · 2016
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Semi-Supervised Classification with Graph Convolutional Networks
Kipf, T. N. and Welling, M · 2016
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CS224W: Social and Information Network Analysis - Graph Clustering, 2016
Leskovec, J · 2016
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Bronstein, M. M., Bruna, J., LeCun, Y., Szlam, A., and Vandergheynst, P · 2017
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Chazal, F. and Michel, B · 2017
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Deep Learning with Topological Signatures
Hofer, C., Kwitt, R., Niethammer, M., and Uhl, A · 2017
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PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures
Carriere, M., Chazal, F., Ike, Y., Lacombe, T., Royer, M., and Umeda, Y · 2019
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Topology of Learning in Artificial Neural Networks, 02 2019
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AttPool: Towards Hierarchical Feature Representation in Graph Convolutional Networks via Attention Mechanism
Huang, J., Li, Z., Li, N., Liu, S., and Li, G · 2019
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Self-Attention Graph Pooling
Lee, J., Lee, I., and Kang, J · 2019
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Graph Convolutional Networks with EigenPooling
Ma, Y., Wang, S., Aggarwal, C. C., and Tang, J · 2019
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ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
Ranjan, E., Sanyal, S., and Talukdar, P. P · 2019
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GNNExplainer: Generating Explanations for Graph Neural Networks
Ying, Z., Bourgeois, D., You, J., Zitnik, M., and Leskovec, J · 2019
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NCVis: Noise Contrastive Approach for Scalable Visualization, 2020
Artemenkov, A. and Panov, M · 2020
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