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05/19/2023
Improving Multimodal Joint Variational Autoencoders through Normalizing Flows and Correlation Analysis
We propose a new multimodal variational autoencoder that enables to gene...
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03/24/2023
Variational Inference for Longitudinal Data Using Normalizing Flows
This paper introduces a new latent variable generative model able to han...
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09/15/2022
A Geometric Perspective on Variational Autoencoders
This paper introduces a new interpretation of the Variational Autoencode...
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06/16/2022
Pythae: Unifying Generative Autoencoders in Python – A Benchmarking Use Case
In recent years, deep generative models have attracted increasing intere...
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04/30/2021
Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder
In this paper, we propose a new method to perform data augmentation in a...
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03/25/2021
Data Generation in Low Sample Size Setting Using Manifold Sampling and a Geometry-Aware VAE
While much efforts have been focused on improving Variational Autoencode...
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10/27/2020
Optimisation des parcours patients pour lutter contre l'errance de diagnostic des patients atteints de maladies rares
A patient suffering from a rare disease in France has to wait an average...
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10/22/2020
Geometry-Aware Hamiltonian Variational Auto-Encoder
Variational auto-encoders (VAEs) have proven to be a well suited tool fo...
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06/19/2020
Mixture of Conditional Gaussian Graphical Models for unlabelled heterogeneous populations in the presence of co-factors
Conditional correlation networks, within Gaussian Graphical Models (GGM)...
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03/23/2020
Deterministic Approximate EM Algorithm; Application to the Riemann Approximation EM and the Tempered EM
The Expectation Maximisation (EM) algorithm is widely used to optimise n...
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03/11/2020
Gaussian Graphical Model exploration and selection in high dimension low sample size setting
Gaussian Graphical Models (GGM) are often used to describe the condition...
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10/20/2019
Learning from both experts and data
In this work we study the problem of inferring a discrete probability di...
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04/05/2019
Simulation of virtual cohorts increases predictive accuracy of cognitive decline in MCI subjects
The ability to predict the progression of biomarkers, notably in NDD, is...
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11/25/2018
A Model-Based Reinforcement Learning Approach for a Rare Disease Diagnostic Task
In this work, we present our various contributions to the objective of b...
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09/25/2017
