@article{mbakam2025learning,title={Learning few-step posterior samplers by unfolding and distillation of diffusion models},author={Mbakam, Charlesquin Kemajou and Pereyra, Marcelo and Spence, Jonathan},journal={Transactions on Machine Learning Research},year={2025},pages={2835-8856},}
2024
2024
SIAM
Marginal Likelihood Estimation in Semiblind Image Deconvolution: A Stochastic Approximation Approach
Charlesquin Kemajou Mbakam, Marcelo Pereyra, and Jean-François Giovannelli
@article{mbakam2024marginal,title={Marginal Likelihood Estimation in Semiblind Image Deconvolution: A Stochastic Approximation Approach},author={Mbakam, Charlesquin Kemajou and Pereyra, Marcelo and Giovannelli, Jean-Fran{\c{c}}ois},journal={SIAM Journal on Imaging Sciences},volume={17},number={2},pages={1206--1254},year={2024},publisher={SIAM},}
JMIV
Empirical Bayesian image restoration by Langevin sampling with a denoising diffusion implicit prior
Charlesquin Kemajou Mbakam, Jean-Francois Giovannelli, and Marcelo Pereyra
@article{mbakam2024empirical,title={Empirical Bayesian image restoration by Langevin sampling with a denoising diffusion implicit prior},author={Mbakam, Charlesquin Kemajou and Giovannelli, Jean-Francois and Pereyra, Marcelo},journal={arXiv preprint arXiv:2409.04384},year={2024},}
ARXIV
Do Bayesian imaging methods report trustworthy probabilities?
David YW Thong, Charlesquin Kemajou Mbakam, and Marcelo Pereyra
@article{thong2024bayesian,title={Do Bayesian imaging methods report trustworthy probabilities?},author={Thong, David YW and Mbakam, Charlesquin Kemajou and Pereyra, Marcelo},journal={arXiv preprint arXiv:2405.08179},year={2024},}