Weighted network estimation by the use of topological graph metrics

Loukianos Spyrou, Javier Escudero

Research output: Contribution to journalArticlepeer-review


Topological metrics of graphs provide a natural way to describe the prominent features of various types of networks. Graph metrics describe the structure and interplay of graph edges and have found applications in many scientific fields. In this work, graph metrics are used in network estimation by developing optimisation methods that incorporate prior knowledge of a network’s topology. The derivatives of graph metrics are used in gradient descent schemes for weighted undirected network denoising, network completion, and network decomposition. The successful performance of our methodology is shown in a number of toy examples and real-world datasets. Most notably, our work establishes a new link between graph theory, network science and optimisation.
Original languageEnglish
Pages (from-to)576-586
Number of pages11
JournalIEEE Transactions on Network Science and Engineering
Issue number3
Early online date21 Jun 2018
Publication statusPublished - 4 Sep 2019


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