Mame Diarra Fall

Orcid: 0000-0003-2749-2589

According to our database1, Mame Diarra Fall authored at least 11 papers between 2011 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of five.

Timeline

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PhD thesis 
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Links

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Bibliography

2025
Regularization by Denoising: Bayesian Model and Langevin-Within-Split Gibbs Sampling.
IEEE Trans. Image Process., 2025

Which Uncertainty Quantification Method in Deep Learning Models for Knee Osteoarthritis Diagnosis?
Proceedings of the IEEE Statistical Signal Processing Workshop, 2025

Vision Transformers for X-ray Diffraction Patterns Analysis.
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

2024
Bayesian Formulation of Regularization by Denoising - Model and Monte Carlo Sampling.
Proceedings of the 26th IEEE International Workshop on Multimedia Signal Processing, 2024

Quantifying Uncertainty in Knee Osteoarthritis Diagnosis.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

2023
Proportion Inference Using Deep Neural Networks. Applications to X-Ray Diffraction and Hyperspectral Imaging.
Proceedings of the 31st European Signal Processing Conference, 2023

2022
A Bayesian Estimation Formulation to Voxel-Based Lesion-Symptom Mapping.
Proceedings of the 30th European Signal Processing Conference, 2022

2018
Voxel-Based Lesion-Symptom Mapping: A Nonparametric Bayesian Approach.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2013
Dynamic and clinical PET data reconstruction: A nonparametric Bayesian approach.
Proceedings of the IEEE International Conference on Image Processing, 2013

2012
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).
PhD thesis, 2012

2011
A discrete-continuous Bayesian model for Emission Tomography.
Proceedings of the 18th IEEE International Conference on Image Processing, 2011


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