Publications

You can also find all my research works on my Google Scholar page.

Thesis

Asymptotically exact data augmentation – Models and Monte Carlo sampling with applications to Bayesian inference
Ph.D. thesis, Institut National Polytechnique de Toulouse, 2020
pdf

Preprints

  1. QLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning
    M. Vono, V. Plassier, A. Durmus, A. Dieuleveut and E. Moulines
    arXiv

  2. High-dimensional Gaussian sampling: a review and a unifying approach based on a stochastic proximal point algorithm
    M. Vono, N. Dobigeon and P. Chainais
    arXiv

  3. Efficient MCMC sampling with dimension-free convergence rate using ADMM-type splitting
    M. Vono*, D. Paulin* and A. Doucet
    arXiv Xian's blog post

Journal papers

  1. Asymptotically exact data augmentation: models, properties and algorithms
    M. Vono, N. Dobigeon and P. Chainais
    Journal of Computational and Graphical Statistics, vol. 30, no. 2, pp. 335-348, 2021
    arXiv pdf doi code

  2. Tracers of the ionization fraction in dense and translucent gas. I. Automated exploitation of massive astrochemical model grids
    E. Bron et al.
    Astronomy & Astrophysics, vol. 645, no. A28, January 2021
    arXiv pdf doi

  3. Quantitative inference of the H2 column densities from 3 mm molecular emission: A case study towards Orion B
    P. Gratier et al.
    Astronomy & Astrophysics, vol. 645, no. A27, January 2021
    arXiv pdf doi

  4. C18O, 13CO, and 12CO abundances and excitation temperatures in the Orion B molecular cloud
    A. Roueff et al.
    Astronomy & Astrophysics, vol. 645, no. A26, January 2021
    arXiv pdf doi

  5. Split-and-augmented Gibbs sampler - Application to large-scale inference problems
    M. Vono, N. Dobigeon and P. Chainais
    IEEE Transactions on Signal Processing, vol. 67, no. 6, pp. 1648-1661, March 2019
    arXiv pdf doi bibtex code

International conference papers

  1. DG-LMC: a turn-key and scalable synchronous distributed MCMC algorithm via Langevin Monte Carlo within Gibbs
    V. Plassier*, M. Vono*, A. Durmus* and E. Moulines
    ICML, Online, 2021 [Long talk, top 14% of accepted papers]
    arXiv pdf doi bibtex code

  2. A fully Bayesian approach for inferring physical properties with credibility intervals from noisy astronomical data
    M. Vono et al.
    IEEE WHISPERS, Amsterdam, Netherlands, 2019
    pdf doi bibtex

  3. Bayesian image restoration under Poisson noise and log-concave prior
    M. Vono, N. Dobigeon and P. Chainais
    IEEE ICASSP, Brighton, U.K., 2019
    pdf doi bibtex code

  4. Efficient sampling through variable splitting-inspired Bayesian hierarchical models
    M. Vono, N. Dobigeon and P. Chainais
    IEEE ICASSP, Brighton, U.K., 2019
    pdf doi bibtex code

  5. Sparse Bayesian binary logistic regression using the split-and-augmented Gibbs sampler
    M. Vono, N. Dobigeon and P. Chainais
    IEEE MLSP, Aalborg, Denmark, 2018 [Finalist for the Best Student Paper Award]
    pdf doi bibtex code

National conference papers

  1. Modèles augmentés asymptotiquement exacts
    M. Vono, N. Dobigeon and P. Chainais
    GRETSI, Lille, France, 2019
    pdf bibtex

  2. Un modèle augmenté asymptotiquement exact pour la restauration bayésienne d’images dégradées par un bruit de Poisson
    M. Vono, N. Dobigeon and P. Chainais
    GRETSI, Lille, France, 2019
    pdf bibtex

* indicates equal contribution.