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Publications

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

Affichage des publications 971 à 980 sur 1553 au total

Life Sciences

Cortical profiles of numerous psychiatric disorders and normal development share a common pattern

The neurobiological bases of the association between development and psychopathology remain poorly understood. Here, we identify a shared spatial pattern of cortical thickness (CT) in normative development and several psychiatric and neurological…

Zhipeng Cao, Renata Cupertino, Jonatan Ottino-Gonzalez, Alistair Murphy, Devarshi Pancholi, Anthony Juliano, Bader Chaarani, Matthew Albaugh, Dekang Yuan, Nathan Schwab, James Stafford, Anna Goudriaan, Kent Hutchison, Chiang-Shan Li, Maartje Luijten, Martine Groefsema, Reza Momenan, Lianne Schmaal, Rajita Sinha, Ruth van Holst, Dick Veltman, Reinout Wiers, Bernice Porjesz, Tristram Lett, Tobias Banaschewski, Arun Bokde, Sylvane Desrivières, Herta Flor, Antoine Grigis, Penny Gowland, Andreas Heinz, Rüdiger Brühl, Jean-Luc Martinot, Marie-Laure Paillère Martinot, Eric Artiges, Frauke Nees, Dimitri Papadopoulos Orfanos, Tomáš Paus, Luise Poustka, Sarah Hohmann, Sabina Millenet, Juliane Fröhner, Lauren Robinson, Michael Smolka, Henrik Walter, Jeanne Winterer, Gunter Schumann, Robert Whelan, Ravi Bhatt, Alyssa Zhu, Patricia Conrod, Neda Jahanshad, Paul Thompson, Scott Mackey, Hugh Garavan

Molecular Psychiatry -

Machine Learning

CAEclust: A Consensus of Autoencoders Representations for Clustering

The CAEclust Python package implements an original deep spectral clustering in an ensemble framework. Recently, strategies combining classical clustering approaches and deep autoencoders have been proposed, but their effectiveness is impeded by deep…

Séverine Affeldt, Lazhar Labiod, Mohamed Nadif

Image Processing On Line -

Machine Learning

Subspace Co-clustering with Two-Way Graph Convolution

Subspace clustering aims to cluster high dimensional data lying in a union of low-dimensional subspaces. It has shown good results on the task of image clustering but text clustering, using documentterm matrices, proved more impervious to advances…

Chakib Fettal, Lazhar Labiod, Mohamed Nadif

CIKM '22: The 31st ACM International Conference on Information and Knowledge Management -

Life Sciences

Anxiety onset in adolescents: a machine-learning prediction

Abstract Recent longitudinal studies in youth have reported MRI correlates of prospective anxiety symptoms during adolescence, a vulnerable period for the onset of anxiety disorders. However, their predictive value has not been established…

Alice Chavanne, Marie Laure Paillère Martinot, Jani Penttilä, Yvonne Grimmer, Patricia Conrod, Argyris Stringaris, Betteke van Noort, Corinna Isensee, Andreas Becker, Tobias Banaschewski, Arun Bokde, Sylvane Desrivières, Herta Flor, Antoine Grigis, Hugh Garavan, Penny Gowland, Andreas Heinz, Rüdiger Brühl, Frauke Nees, Dimitri Papadopoulos Orfanos, Tomáš Paus, Luise Poustka, Sarah Hohmann, Sabina Millenet, Juliane Fröhner, Michael Smolka, Henrik Walter, Robert Whelan, Gunter Schumann, Jean-Luc Martinot, Eric Artiges, Semiha Aydin, Christine Bach, Alexis Barbot, Gareth Barker, Nadège Bordas, Zuleima Bricaud, Uli Bromberg, Ruediger Bruehl, Christian Büchel, Anna Cattrell, Tahmine Fadai, Irina Filippi, Vincent Frouin, André Galinowski, Jürgen Gallinat, Fanny Gollier Briand, Chantal Gourlan, Stella Guldner, Bernd Ittermann, Tianye Jia, Hervé Lemaitre, Jessica Massicotte, Ruben Miranda, Kathrin Müller, Charlotte Nymberg, Zdenka Pausova, Jean-Baptiste Poline, Jan Reuter, John Rogers, Barbara Ruggeri, Anna Sarvasmaa, Christine Schmäl, Maren Struve, Wolfgang Sommer, Hélène Vulser

Molecular Psychiatry -

Computer Science

An effective strategy for churn prediction and customer profiling

Customer churn prediction and profiling are two major economic concerns for many companies. Different learning approaches have been proposed, however the a priori choice of the most suitable model to perform both tasks remains non-trivial as it is…

Louis Geiler, Séverine Affeldt, Mohamed Nadif

Data and Knowledge Engineering -

Computer Science

Fast and Accurate Importance Weighting for Correcting Sample Bias

Bias in datasets can be very detrimental for appropriate statistical estimation. In response to this problem, importance weighting methods have been developed to match any biased distribution to its corresponding target unbiased distribution. The…

Antoine de Mathelin, Francois Deheeger, Mathilde Mougeot, Nicolas Vayatis

Joint European Conference on Machine Learning and Knowledge Discovery in Databases -

Computer Science

Unsupervised Domain Adaptation for Constraining Star Formation Histories

The prevalent paradigm of machine learning today is to use past observations to predict future ones. What if, however, we are interested in knowing the past given the present? This situation is indeed one that astronomers must contend with often. To…

Sankalp Gilda, Antoine de Mathelin, Sabine Bellstedt, Guillaume Richard

1st Annual AAAI Workshop on AI to Accelerate Science and Engineering (AI2ASE) -