Explore the words cloud of the HIntNets project. It provides you a very rough idea of what is the project "HIntNets" about.
The following table provides information about the project.
Coordinator |
THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Organization address contact info |
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 |
Take a look of project's partnership.
# | ||||
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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 |
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.
year | authors and title | journal | last update |
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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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