BACK TO INDEX

Publications of Luigi Antelmi

Thesis

  1. Luigi Antelmi. Statistical learning on heterogeneous medical data with bayesian latent variable models : application to neuroimaging dementia studies. Theses, Université Côte d'Azur, July 2021. Keyword(s): Alzheimer's disease, Neuro-imaging, Magnetic resonance imaging, Positron emission tomography, Variational autoencoder, Multi-task learning, High dimensional data, Maladie d'Alzheimer, Neuro-imagerie, Imagerie par résonnance magnétique, Tomographie par émission de positrons, Auto-encodeur variationnel, Apprentissage multi-tâche, Données de haute dimension, Données multimodales. [bibtex-entry]


Articles in journal, book chapters

  1. Luigi Antelmi, Nicholas Ayache, Philippe Robert, and Marco Lorenzi. Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data. Proceedings of Machine Learning Research, (97):302-311, 2019. [bibtex-entry]


Conference articles

  1. Luigi Antelmi, Nicholas Ayache, Philippe Robert, and Marco Lorenzi. Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data. In ICML 2019 - 36th International Conference on Machine Learning, Long Beach, United States, June 2019. [bibtex-entry]


  2. Luigi Antelmi, Nicholas Ayache, Philippe Robert, and Marco Lorenzi. Multi-Channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's Disease. In Understanding and Interpreting Machine Learning in Medical Image Computing Applications, volume 11038 of LNCS, Granada, Spain, pages 15-23, September 2018. [bibtex-entry]


Miscellaneous

  1. Luigi Antelmi, Nicholas Ayache, Philippe Robert, Federica Ribaldi, Valentina Garibotto, Giovanni B Frisoni, and Marco Lorenzi. Combining Multi-Task Learning and Multi-Channel Variational Auto-Encoders to Exploit Datasets with Missing Observations -Application to Multi-Modal Neuroimaging Studies in Dementia. Note: Working paper or preprint, May 2021. Keyword(s): Multi Task Learning, Missing Data, Variational Autoencoders, Multimodal Data Analysis, OPAL-Meso. [bibtex-entry]


  2. Valeria Manera, Luigi Antelmi, Radia Zeghari, Nicholas Ayache, Marco Lorenzi, and Philippe Robert. Prevalence of lack of interest and anhedonia in the general population of the UK Biobank. AAIC 2019 - Alzheimer's Association International Conference, July 2019. Note: Poster. [bibtex-entry]


  3. Luigi Antelmi, Nicholas Ayache, Philippe Robert, and Marco Lorenzi. Supplementary Material of the paper: ''Multi-Channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's Disease'', July 2018. Note: Supplementary Material of the paper: ''Multi-Channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's Disease''. Paper accepted at the 1st International Workshop on Machine Learning in Clinical Neuroimaging, in conjunction with MICCAI 2018, September 20, Granada (Spain). [bibtex-entry]


  4. Luigi Antelmi, Marco Lorenzi, Valeria Manera, Philippe Robert, and Nicholas Ayache. A method for statistical learning in large databases of heterogeneous imaging, cognitive and behavioral data.. EPICLIN 2018 - 12ème Conférence Francophone d'Epidémiologie Clinique / CLCC 2018 - 25èmes Journées des statisticiens des Centre de Lutte Contre le Cancer, May 2018. Note: Poster. Keyword(s): CCA, Statistical learning. [bibtex-entry]



BACK TO INDEX

Disclaimer:

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All person copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Les documents contenus dans ces répertoires sont rendus disponibles par les auteurs qui y ont contribué en vue d'assurer la diffusion à temps de travaux savants et techniques sur une base non-commerciale. Les droits de copie et autres droits sont gardés par les auteurs et par les détenteurs du copyright, en dépit du fait qu'ils présentent ici leurs travaux sous forme électronique. Les personnes copiant ces informations doivent adhérer aux termes et contraintes couverts par le copyright de chaque auteur. Ces travaux ne peuvent pas être rendus disponibles ailleurs sans la permission explicite du détenteur du copyright.

Last modified: Sat Dec 21 12:30:03 2024
Author: epione-publi.

This document was translated from BibTEX by bibtex2html