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7 résultats
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triés par
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Combining Multi-Task Learning and Multi-Channel Variational Auto-Encoders to Exploit Datasets with Missing Observations -Application to Multi-Modal Neuroimaging Studies in Dementia2021
Pré-publication, Document de travail
hal-03114888v2
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Prevalence of lack of interest and anhedonia in the general population of the UK BiobankAAIC 2019 - Alzheimer’s Association International Conference, Jul 2019, Los Angeles, United States
Poster de conférence
hal-02174565v1
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Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous DataICML 2019 - 36th International Conference on Machine Learning, Jun 2019, Long Beach, United States
Communication dans un congrès
hal-02154181v1
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Supplementary Material of the paper: "Multi-Channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's Disease2018
Autre publication scientifique
hal-01844733v1
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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, Nice, France. Elsevier, Revue d'Épidémiologie et de Santé Publique, 66 (3), pp.S180, 2018, 12e Conférence francophone d’Épidémiologie clinique 25e Journée des statisticiens des Centres de lutte contre le cancer. ⟨10.1016/j.respe.2018.03.306⟩
Poster de conférence
hal-01827389v1
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Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous DataProceedings of Machine Learning Research, 2019, Proceedings of ICML 2019, 97, pp.302--311
Article dans une revue
hal-02395747v1
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Multi-Channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's DiseaseUnderstanding and Interpreting Machine Learning in Medical Image Computing Applications, Sep 2018, Granada, Spain. pp.15-23
Communication dans un congrès
hal-02397737v2
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