Picture of fish in sea

Open Access research that uses mathematical models to solve ecological problems...

Solving a variety of ecological and biological problems is the focus of marine population modelling research conducted within the Department of Mathematics & Statistics. Here research deploys mathematical models to better understanding issues relating to fish stock management, ecosystem dynamics, ocean currents, and the effects of multispecies interactions within diverse marine ecosystems.

Research work in marine population modelling interfaces with a number of other key research specialisms, including mathematical biology, epidemiology and statistical informatics, where investigations are improving human understanding of the behaviour of infectious diseases, particularly in relation to animal infections; but also the modelling of complex biological processes such as antibiotic prodcution in actinobacteria.

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Number of items: 10.

2019

Arrigo, Francesca and Tudisco, Francesco; (2019) Multi-dimensional, multilayer, nonlinear and dynamic HITS. In: SIAM International Conference on Data Mining, SDM 2019. SIAM, CAN, pp. 369-377. ISBN 9781611975673

2018

Tudisco, Francesco and Arrigo, Francesca and Gautier, Antoine (2018) Node and layer eigenvector centralities for multiplex networks. SIAM Journal on Applied Mathematics, 78 (2). 853–876. ISSN 0036-1399

Fasino, Dario and Tudisco, Francesco (2018) The expected adjacency and modularity matrices in the degree corrected stochastic block model. Special Matrices, 6 (1). pp. 110-121. ISSN 2300-7451

2017

Fasino, Dario and Tudisco, Francesco (2017) Modularity bounds for clusters located by leading eigenvectors of the normalized modularity matrix. Journal of Mathematical Inequalities, 11 (3). pp. 701-714. ISSN 1848-9575

Fasino, Dario and Tudisco, Francesco (2017) A modularity based spectral method for simultaneous community and anti-community detection. Linear Algebra and its Applications. ISSN 0024-3795

Pozza, Stefano and Tudisco, Francesco (2017) On the stability of network indices defined by means of matrix functions. Working paper. arXiv.org, Ithaca, N.Y..

Tudisco, F. and Mercado, P. and Hein, M. (2017) Community detection in networks via nonlinear modularity eigenvectors. Working paper. arXiv.org, Ithaca, N.Y..

Cipolla, Stefano and Di Fiore, Carmine and Tudisco, Francesco (2017) Euler-Richardson method preconditioned by weakly stochastic matrix algebras : a potential contribution to Pagerank computation. The Electronic Journal of Linear Algebra, 32. 20. ISSN 1081-3810

Tudisco, Francesco and Hein, Matthias (2017) A nodal domain theorem and a higher-order Cheeger inequality for the graph p-Laplacian. Journal of Spectral Theory. ISSN 1664-0403 (In Press)

2016

Mercado, Pedro and Tudisco, Francesco and Hein, Matthias (2016) Clustering signed networks with the geometric mean of Laplacians. In: NIPS 2016 - Neural Information Processing Systems, 2016-12-05 - 2016-12-10, Centre Convencions Internacional Barcelona.

This list was generated on Sun Jul 12 18:34:55 2020 BST.