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Publications

Cette page présente les publications du Centre Borelli déposées sur le serveur HAL.

Affichage des publications 811 à 820 sur 1268 au total

Signal and Image processing

Non-smooth interpolation of graph signals

We consider the problem of signal interpolation on graphs, i.e. recovering one or multiple graph signal values from incomplete measurements. We propose a review of the graph signal interpolation methods, which enlightens the restrictive underlying…

Antoine Mazarguil, Laurent Oudre, Nicolas Vayatis

Signal Processing -

Optimization and Control

Improving NMF clustering by leveraging contextual relationships among words

Non-negative Matrix Factorization (NMF) and its variants have been successfully used for clustering text documents. However, NMF approaches like other models do not explicitly account for the contextual dependencies between words. To remedy this…

Mickael Febrissy, Aghiles Salah, Melissa Ailem, Mohamed Nadif

Neurocomputing -

Human health and pathology

Predicting Depression Onset in Young People Based on Clinical, Cognitive, Environmental, and Neurobiological Data

Background: Adolescent onset of depression is associated with long-lasting negative consequences. Identifying adolescents at risk for developing depression would enable the monitoring of risk factors and the development of early intervention…

Yara Toenders, Akhil Kottaram, Richard Dinga, Christopher Davey, Tobias Banaschewski, Arun L.W. Bokde, Erin Burke Quinlan, Sylvane Desrivières, Herta Flor, Antoine Grigis, Hugh Garavan, Penny Gowland, Andreas Heinz, Rüdiger Brühl, Jean-Luc Martinot, Marie-Laure Paillère Martinot, Frauke Nees, Dimitri Papadopoulos Orfanos, Herve Lemaitre, Tomáš Paus, Luise Poustka, Sarah Hohmann, Juliane Fröhner, Michael Smolka, Henrik Walter, Robert Whelan, Argyris Stringaris, Betteke van Noort, Jani Penttilä, Yvonne Grimmer, Corinna Insensee, Andreas Becker, Gunter Schumann, Lianne Schmaal

Biological Psychiatry: Cognitive Neuroscience and Neuroimaging -

Machine Learning

Semi-supervised Latent Block Model with pairwise constraints

Co-clustering aims at simultaneously partitioning both dimensions of a data matrix. It has demonstrated better performances than one-sided clustering for high-dimensional data. The Latent Block Model (LBM) is a probabilistic model for co-clustering…

Paul Riverain, Simon Fossier, Mohamed Nadif

Machine Learning -

Machine Learning

Poisson degree corrected dynamic stochastic block model

Stochastic Block Model (SBM) provides a statistical tool for modeling and clustering network data. In this paper, we propose an extension of this model for discrete-time dynamic networks that takes into account the variability in node degrees,…

Paul Riverain, Simon Fossier, Mohamed Nadif

Advances in Data Analysis and Classification -

Life Sciences

Neurological side effects of radiation therapy

Radiation therapy (RT) is one of the main treatments administered to patients with cancer. The development of technology has improved RT accuracy by allowing more precise delivery of high doses to the target volumes with reduced exposure of healthy…

J. Jacob, L. Feuvret, J.-M. Simon, M. Ribeiro, L. Nichelli, C. Jenny, D. Ricard, D. Psimaras, K. Hoang-Xuan, P. Maingon

Neurological Sciences -

Neurobiology

Function of the Retinal Pigment Epithelium in Patients With Neurofibromatosis Type 1

PURPOSE. Retinal and choroidal abnormalities in neurofibromatosis type 1 (NF1) remain poorly studied. It has been reported, however, that the function of the retinal pigment epithelium (RPE) in NF1 was abnormal, with a supra-normal Arden ratio of…

Romain Touzé, Marc Abitbol, Dominique Bremond-Gignac, Matthieu Robert

Investigative Ophthalmology & Visual Science -