| Review of wavelet-based unsupervised texture segmentation, advantage of adaptive wavelets Y Huang, V De Bortoli, F Zhou, J Gilles IET Image Processing 12 (9), 1626-1638, 2018 | 11 | 2018 |
| Efficient stochastic optimisation by unadjusted langevin monte carlo. application to maximum marginal likelihood and empirical bayesian estimation V De Bortoli, A Durmus, M Pereyra, AF Vidal arXiv preprint arXiv:1906.12281, 2019 | 10* | 2019 |
| Maximum likelihood estimation of regularisation parameters in high-dimensional inverse problems: an empirical Bayesian approach AF Vidal, V De Bortoli, M Pereyra, A Durmus arXiv preprint arXiv:1911.11709, 2019 | 4 | 2019 |
| Continuous and Discrete-Time Analysis of Stochastic Gradient Descent for Convex and Non-Convex Functions X Fontaine, V De Bortoli, A Durmus arXiv preprint arXiv:2004.04193, 2020 | 3 | 2020 |
| Convergence of diffusions and their discretizations: from continuous to discrete processes and back V De Bortoli, A Durmus arXiv preprint arXiv:1904.09808, 2019 | 3 | 2019 |
| Approximate Bayesian computation with the sliced-Wasserstein distance K Nadjahi, V De Bortoli, A Durmus, R Badeau, U Şimşekli ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 2 | 2020 |
| Redundancy in Gaussian random fields V De Bortoli, A Desolneux, B Galerne, A Leclaire ESAIM: Probability and Statistics 24, 627-660, 2020 | 2 | 2020 |
| Macrocanonical models for texture synthesis V De Bortoli, A Desolneux, B Galerne, A Leclaire International Conference on Scale Space and Variational Methods in Computer …, 2019 | 2 | 2019 |
| Patch redundancy in images: a statistical testing framework and some applications V De Bortoli, A Desolneux, B Galerne, A Leclaire SIAM Journal on Imaging Sciences 12 (2), 893-926, 2019 | 2 | 2019 |
| Quantitative propagation of chaos for sgd in wide neural networks V De Bortoli, A Durmus, X Fontaine, U Simsekli arXiv preprint arXiv:2007.06352, 2020 | 1 | 2020 |
| Maximum Likelihood Estimation of Regularization Parameters in High-Dimensional Inverse Problems: An Empirical Bayesian Approach Part I: Methodology and Experiments AF Vidal, V De Bortoli, M Pereyra, A Durmus SIAM Journal on Imaging Sciences 13 (4), 1945-1989, 2020 | 1 | 2020 |
| Maximum Likelihood Estimation of Regularization Parameters in High-Dimensional Inverse Problems: An Empirical Bayesian Approach. Part II: Theoretical Analysis V De Bortoli, A Durmus, M Pereyra, AF Vidal SIAM Journal on Imaging Sciences 13 (4), 1990-2028, 2020 | 1 | 2020 |
| Maximum entropy methods for texture synthesis: theory and practice V De Bortoli, A Desolneux, A Durmus, B Galerne, A Leclaire arXiv preprint arXiv:1912.01691, 2019 | 1 | 2019 |
| Statistiques non locales dans les images: modélisation, estimation et échantillonnage V de Bortoli Université Paris Saclay, 2020 | | 2020 |
Alain DurmusENS Paris-SaclayAdresse e-mail validée de cmla.ens-cachan.fr
