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In graph analysis, a classic task consists in computing similarity measures between (groups of) nodes.
Resistance distance
D. J. Klein and M. Randić · 1993
Earlier work this paper cites.
Random walks on graphs: A survey
L. Lovász · 1993
Earlier work this paper cites.
Graph approximations to geodesics on embedded manifolds
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Earlier work this paper cites.
Perturbation Analysis of Optimization Problems
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Earlier work this paper cites.
Latent space approaches to social network analysis
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Earlier work this paper cites.
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Earlier work this paper cites.
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Convergence of Laplacian eigenmaps
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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G. Peyré, M. Péchaud, R. Keriven, and L. D. Cohen · 2010
Earlier work this paper cites.
On learning with integral operators
L. Rosasco, M. Belkin, and E. De Vito · 2010
Earlier work this paper cites.
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Earlier work this paper cites.
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F. Mémoli · 2011
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L. Lovász · 2012
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M. Cuturi · 2013
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M. Tang, D. L. Sussman, and C. E. Priebe · 2013
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A scalable approach to probabilistic latent space inference of large-scale networks
J. Yin, Q. Ho, and E. P. Xing · 2013
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The Gromov-Wasserstein Distance: A Brief Overview
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U. Von Luxburg, A. Radl, and M. Hein · 2014
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Error Estimates for Spectral Convergence of the Graph Laplacian on Random Geometric Graphs Toward the Laplace–Beltrami Operator
N. García Trillos, M. Gerlach, M. Hein, and D. Slepčev · 2019
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Statistical bounds for entropic optimal transport: Sample complexity and the central limit theorem
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Computational Optimal Transport
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The geometry of continuous latent space models for network data
A. L. Smith, D. M. Asta, and C. A. Calder · 2019
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Deep graph infomax
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Continuum Limit of Total Variation on Point Clouds
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A Comprehensive Survey on Graph Neural Networks
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