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VERSION:2.0
PRODID:-//AMSE//Event Calendar//FR
CALSCALE:GREGORIAN
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BEGIN:VEVENT
UID:event-12017@amse-aixmarseille.fr
DTSTAMP:20260415T015601Z
CREATED:20260415T015601Z
LAST-MODIFIED:20260415T015601Z
STATUS:CONFIRMED
SEQUENCE:0
SUMMARY:phd seminar - Anita Salvador
DTSTART:20250325T104500Z
DTEND:20250325T111500Z
DESCRIPTION:Non-ischemic cardiomyopathies represent almost 40% of hospitali
 zed patients with heart failure. These pathologies exhibit high variability
  in clinical presentation and progression due to their multi-factorial natu
 re. Characterizing a patient’s health state requires gathering informatio
 n from different sources (MRI images\, patient record\, ECG\, etc.) and agg
 regating them to obtain a simpler representation. I am working on different
  models within the family of Multimodal Variational Autoencoders (VAEs) whi
 ch offer a probabilistic framework for learning joint latent representation
 s from heterogeneous data. In this presentation\, I will discuss two archit
 ectures for multimodal VAEs: alignment-based and fusion-based approaches. W
 hile the alignment model learns a latent space for each modality\, the fusi
 on model aggregates distributions from each modality into a unified represe
 ntation. However\, the choice of aggregation method raises theoretical chal
 lenges\, one of them being computing the Kullback-Leibler divergence betwee
 n latent distributions.\\n\\nContact: Philippine Escudié : philippine.esc
 udie[at]univ-amu.frLucie Giorgi : lucie.giorgi[at]univ-amu.frKla Kouadio : 
 kla.kouadio[at]univ-amu.frLola Soubeyrand : lola.soubeyrand[at]univ-amu.fr
 \n\nPlus d'informations: https://amse-aixmarseille.fr/fr/evenements/anita-s
 alvador
LOCATION:MEGA - Salle Carine Nourry\, 424\, Chemin du Viaduc\, 13080 Aix-en
 -Provence
URL;VALUE=URI:https://amse-aixmarseille.fr/fr/evenements/anita-salvador
CONTACT:Philippine Escudié :&nbsp\;philippine.escudie[at]univ-amu.frLucie 
 Giorgi : lucie.giorgi[at]univ-amu.frKla Kouadio : kla.kouadio[at]univ-amu.f
 rLola Soubeyrand :&nbsp\;lola.soubeyrand[at]univ-amu.fr
TRANSP:OPAQUE
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