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HIntNets SIGNED

Higher-order interactions and Laplacian dynamics in complex networks: structure, dynamics and control

Total Cost €

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EC-Contrib. €

0

Partnership

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Project "HIntNets" data sheet

The following table provides information about the project.

Coordinator
THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD 

Organization address
address: WELLINGTON SQUARE UNIVERSITY OFFICES
city: OXFORD
postcode: OX1 2JD
website: www.ox.ac.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Project website https://michaelschaub.github.io/HIntNets/
 Total cost 251˙857 €
 EC max contribution 251˙857 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2015
 Funding Scheme MSCA-IF-GF
 Starting year 2017
 Duration (year-month-day) from 2017-07-01   to  2020-08-18

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD UK (OXFORD) coordinator 251˙857.00
2    MASSACHUSSETTS INSTITUTE OF TECHNOLOGY MIT CORPORATION US (CAMBRIDGE) partner 0.00

Map

 Project objective

Complex networks are an essential ingredient of modern life, and underpin integral parts of our biological, physical, technological and socio-economic universe. Thus far, such networks have been mainly represented as graphs. However, while graphs can capture pairwise interactions between nodes, fundamental interactions in networks often take place between multiple nodes. For example, in socio-economic networks, the joint coordinated activity of several agents (e.g. buyer, seller, broker); the formation and interactions of coalitions; the emergence of peer pressure; and the existence of triadic closure are all prevalent.

The objective of this interdisciplinary project is to investigate such non-binary interactions in complex networks and their dynamical implications. Specifically, we will investigate how such interactions can be taken into account for the modelling, analysis and design of complex networks.

To achieve this, we will extend the geometrical framework of simplicial complexes to account systematically for weighted non-binary couplings of nodes, node-pairs, triplets, etc., allowing us to consistently assess and design higher-order interactions. Here, we will focus on consensus and random walks as prototypical examples of a range of other phenomena. Working at the interface of Network Science and Control Theory, we will combine recent tools from both fields and apply our results to real biological and socio-economic networks and data. We will investigate how the consideration of non-binary couplings can yield an improved understanding of the propagation of external shocks in socio-economic networks, and help to reveal dynamical groupings in networks emerging from systems biology experiments.

Providing a synergy between the applicant’s multidisciplinary background and the leading Systems, Optimization and Control research of the hosts, this proposal holds the potential to leverage the candidate’s career and yield scientific results of general relevance.

 Publications

year authors and title journal last update
List of publications.
2019 Michael T. Schaub, Santiago Segarra, John N. Tsitsiklis
Blind identification of stochastic block models from dynamical observations
published pages: , ISSN: , DOI:
2019-09-09
2019 Yu Zhu, Michael T. Schaub, Ali Jadbabaie, Santiago Segarra
Network Inference from Consensus Dynamics with Unknown Parameters
published pages: , ISSN: , DOI:
2019-09-09
2018 Schaub, Michael T.; Benson, Austin R.; Horn, Paul; Lippner, Gabor; Jadbabaie, Ali
Random Walks on Simplicial Complexes and the normalized Hodge 1-Laplacian
published pages: , ISSN: , DOI:
2019-09-02
2018 Yazan N. Billeh, Michael T. Schaub
Feedforward architectures driven by inhibitory interactions
published pages: 63-74, ISSN: 0929-5313, DOI: 10.1007/s10827-017-0669-1
Journal of Computational Neuroscience 44/1 2019-09-02
2019 Junteng Jia, Michael T. Schaub, Santiago Segarra, Austin R. Benson
Graph-based Semi-Supervised & Active Learning for Edge Flows
published pages: , ISSN: , DOI: 10.1145/3292500.3330872
25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’19) August 4–8, 2019 2019-09-02
2018 Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, Jon Kleinberg
Simplicial closure and higher-order link prediction
published pages: E11221-E11230, ISSN: 0027-8424, DOI: 10.1073/pnas.1800683115
Proceedings of the National Academy of Sciences 115/48 2019-09-02
2019 Michael T. Schaub, Jean-Charles Delvenne, Renaud Lambiotte, Mauricio Barahona
Multiscale dynamical embeddings of complex networks
published pages: 62308, ISSN: 2470-0053, DOI: 10.1103/PhysRevE.99.062308
Physical Review E 99/6 2019-09-02
2018 Marco Avella-Medina, Francesca Parise, Michael Schaub, Santiago Segarra
Centrality measures for graphons: Accounting for uncertainty in networks
published pages: 1-1, ISSN: 2327-4697, DOI: 10.1109/tnse.2018.2884235
IEEE Transactions on Network Science and Engineering 2019-09-02
2017 Mauro Faccin, Michael T Schaub, Jean-Charles Delvenne
Entrograms and coarse graining of dynamics on complex networks
published pages: 661-678, ISSN: 2051-1310, DOI: 10.1093/comnet/cnx055
Journal of Complex Networks 6/5 2019-09-02
2018 Schaub, Michael T.; Delvenne, Jean-Charles; Lambiotte, Renaud; Barahona, Mauricio
Structured networks and coarse-grained descriptions: a dynamical perspective
published pages: , ISSN: , DOI:
2019-09-02
2017 Ernesto Estrada, Jean-Charles Delvenne, Naomichi Hatano, José L Mateos, Ralf Metzler, Alejandro P Riascos, Michael T Schaub
Random multi-hopper model: super-fast random walks on graphs
published pages: 382-403, ISSN: 2051-1310, DOI: 10.1093/comnet/cnx043
Journal of Complex Networks 6/3 2019-09-02
2017 Rosvall, Martin; Delvenne, Jean-Charles; Schaub, Michael T.; Lambiotte, Renaud
Different approaches to community detection
published pages: , ISSN: , DOI:
2019-09-02

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The information about "HINTNETS" are provided by the European Opendata Portal: CORDIS opendata.

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