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09/13/2023
Tackling the dimensions in imaging genetics with CLUB-PLS
A major challenge in imaging genetics and similar fields is to link high...
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06/05/2023
On Tail Decay Rate Estimation of Loss Function Distributions
The study of loss function distributions is critical to characterize a m...
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06/05/2023
Enhanced Distribution Modelling via Augmented Architectures For Neural ODE Flows
While the neural ODE formulation of normalizing flows such as in FFJORD ...
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06/05/2023
Faster Training of Diffusion Models and Improved Density Estimation via Parallel Score Matching
In Diffusion Probabilistic Models (DPMs), the task of modeling the score...
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04/24/2023
Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications
The real-world implementation of federated learning is complex and requi...
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04/17/2023
Fed-MIWAE: Federated Imputation of Incomplete Data via Deep Generative Models
Federated learning allows for the training of machine learning models on...
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11/21/2022
Sequential Informed Federated Unlearning: Efficient and Provable Client Unlearning in Federated Optimization
The aim of Machine Unlearning (MU) is to provide theoretical guarantees ...
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06/21/2022
A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates
We propose a novel framework to study asynchronous federated learning op...
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05/17/2022
Privacy Preserving Image Registration
Image registration is a key task in medical imaging applications, allowi...
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04/15/2022
A Differentially Private Probabilistic Framework for Modeling the Variability Across Federated Datasets of Heterogeneous Multi-View Observations
We propose a novel federated learning paradigm to model data variability...
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07/26/2021
On The Impact of Client Sampling on Federated Learning Convergence
While clients' sampling is a central operation of current state-of-the-a...
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05/12/2021
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning
This work addresses the problem of optimizing communications between ser...
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04/30/2021
Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction: Application to the Allen human brain atlas
Joint registration of a stack of 2D histological sections to recover 3D ...
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01/22/2021
Vessel-CAPTCHA: an efficient learning framework for vessel annotation and segmentation
The use of deep learning techniques for 3D brain vessel image segmentati...
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10/02/2020
Joint data imputation and mechanistic modelling for simulating heart-brain interactions in incomplete datasets
The use of mechanistic models in clinical studies is limited by the lack...
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06/21/2020
Free-rider Attacks on Model Aggregation in Federated Learning
Free-rider attacks on federated learning consist in dissimulating partic...
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05/23/2019
A model of brain morphological changes related to aging and Alzheimer's disease from cross-sectional assessments
In this study we propose a deformation-based framework to jointly model ...
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02/28/2019
Monotonic Gaussian Process for Spatio-Temporal Trajectory Separation in Brain Imaging Data
We introduce a probabilistic generative model for disentangling spatio-t...
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01/11/2019
DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders
Here we present DIVE: Data-driven Inference of Vertexwise Evolution. DIV...
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01/11/2019
Disease Knowledge Transfer across Neurodegenerative Diseases
We introduce Disease Knowledge Transfer (DKT), a novel technique for tra...
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10/19/2018
Federated Learning in Distributed Medical Databases: Meta-Analysis of Large-Scale Subcortical Brain Data
At this moment, databanks worldwide contain brain images of previously u...
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08/20/2018
Alzheimer's Disease Modelling and Staging through Independent Gaussian Process Analysis of Spatio-Temporal Brain Changes
Alzheimer's disease (AD) is characterized by complex and largely unknown...
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08/10/2018
Multi-Channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's Disease
The joint analysis of biomedical data in Alzheimer's Disease (AD) is imp...
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02/15/2018