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2020 – today
- 2024
[c6]Mame Diarra Fall:
Quantifying Uncertainty in Knee Osteoarthritis Diagnosis. ISBI 2024: 1-5- [i1]Elhadji C. Faye, Mame Diarra Fall, Nicolas Dobigeon:
Regularization by denoising: Bayesian model and Langevin-within-split Gibbs sampling. CoRR abs/2402.12292 (2024) - 2023
- [c5]Titouan Simonnet, Mame Diarra Fall, Bruno Galerne, Francis Claret
, Sylvain Grangeon:
Proportion Inference Using Deep Neural Networks. Applications to X-Ray Diffraction and Hyperspectral Imaging. EUSIPCO 2023: 1310-1314 - 2022
- [c4]Mame Diarra Fall, Nicolas Dobigeon, Pascal Auzou:
A Bayesian Estimation Formulation to Voxel-Based Lesion-Symptom Mapping. EUSIPCO 2022: 2201-2205
2010 – 2019
- 2018
- [c3]Mame Diarra Fall, Emilie Lavau, Pascal Auzou:
Voxel-Based Lesion-Symptom Mapping: A Nonparametric Bayesian Approach. ICASSP 2018: 1050-1054 - 2013
- [c2]Mame Diarra Fall, Eric Barat, Claude Comtat, Thomas Dautremer, Thierry Montagu, Simon Stute:
Dynamic and clinical PET data reconstruction: A nonparametric Bayesian approach. ICIP 2013: 345-349 - 2012
- [b1]Mame Diarra Fall:
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). University of Paris-Sud, Orsay, France, 2012 - 2011
- [c1]Mame Diarra Fall, Eric Barat, Claude Comtat, Thomas Dautremer, Thierry Montagu, Ali Mohammad-Djafari:
A discrete-continuous Bayesian model for Emission Tomography. ICIP 2011: 1373-1376
Coauthor Index
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