Lossless Representation of Graphs using Distributions

10/09/2007
by   Mireille Boutin, et al.
0

We consider complete graphs with edge weights and/or node weights taking values in some set. In the first part of this paper, we show that a large number of graphs are completely determined, up to isomorphism, by the distribution of their sub-triangles. In the second part, we propose graph representations in terms of one-dimensional distributions (e.g., distribution of the node weights, sum of adjacent weights, etc.). For the case when the weights of the graph are real-valued vectors, we show that all graphs, except for a set of measure zero, are uniquely determined, up to isomorphism, from these distributions. The motivating application for this paper is the problem of browsing through large sets of graphs.

READ FULL TEXT
research
02/27/2018

Network Representation Using Graph Root Distributions

Exchangeable random graphs serve as an important probabilistic framework...
research
05/30/2023

Discretization and Optimization using Graphs: One-Dimensional Algorithm

We consider the problem of discretizing one-dimensional, real-valued fun...
research
06/29/2021

Diff2Dist: Learning Spectrally Distinct Edge Functions, with Applications to Cell Morphology Analysis

We present a method for learning "spectrally descriptive" edge weights f...
research
05/16/2023

Interplay between Topology and Edge Weights in Real-World Graphs: Concepts, Patterns, and an Algorithm

What are the relations between the edge weights and the topology in real...
research
09/14/2020

Sparsity of weighted networks: measures and applications

A majority of real life networks are weighted and sparse. The present ar...
research
07/05/2022

Probability density estimation for sets of large graphs with respect to spectral information using stochastic block models

For graph-valued data sampled iid from a distribution μ, the sample mome...
research
05/04/2012

Weighted Patterns as a Tool for Improving the Hopfield Model

We generalize the standard Hopfield model to the case when a weight is a...

Please sign up or login with your details

Forgot password? Click here to reset