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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]



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Last modified: Sun Jul 3 00:30:10 2022
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