A discrete-continuous Bayesian model for Emission Tomography. - Mame Diarra Fall; Eric Barat; Claude Comtat; Thomas Dautremer; Thierry Montagu; Ali Mohammad-Djafari (ICIP, 2011)

Modélisation stochastique de processus pharmaco-cinétiques, application à la reconstruction tomographique par émission de positrons (TEP) spatio-temporelle. (Stochastic modeling of pharmaco-kinetic processes, applied to PET space-time reconstruction). - Mame Diarra Fall (2012)

Dynamic and clinical PET data reconstruction: A nonparametric Bayesian approach. - Mame Diarra Fall; Eric Barat; Claude Comtat; Thomas Dautremer; Thierry Montagu; Simon Stute (ICIP, 2013)

Voxel-Based Lesion-Symptom Mapping: A Nonparametric Bayesian Approach. - Mame Diarra Fall; Emilie Lavau; Pascal Auzou (ICASSP, 2018)

A Bayesian Estimation Formulation to Voxel-Based Lesion-Symptom Mapping. - Mame Diarra Fall; Nicolas Dobigeon; Pascal Auzou (EUSIPCO, 2022)

Proportion Inference Using Deep Neural Networks. Applications to X-Ray Diffraction and Hyperspectral Imaging. - Titouan Simonnet; Mame Diarra Fall; Bruno Galerne; Francis Claret; Sylvain Grangeon (EUSIPCO, 2023)

Quantifying Uncertainty in Knee Osteoarthritis Diagnosis. - Mame Diarra Fall (ISBI, 2024)

Bayesian Formulation of Regularization by Denoising - Model and Monte Carlo Sampling. - Elhadji C. Faye; Mame Diarra Fall; Aladine Chetouani; Nicolas Dobigeon (MMSP, 2024)

Vision Transformers for X-ray Diffraction Patterns Analysis. - Titouan Simonnet; Mame Diarra Fall; Sylvain Grangeon; Bruno Galerne (ICASSP, 2025)

Which Uncertainty Quantification Method in Deep Learning Models for Knee Osteoarthritis Diagnosis? - Mame Diarra Fall; Elhadji C. Faye (SSP, 2025)

Regularization by Denoising: Bayesian Model and Langevin-Within-Split Gibbs Sampling. - Elhadji C. Faye; Mame Diarra Fall; Nicolas Dobigeon (IEEE Trans. Image Process., 2025)