Valentin DE BORTOLI
Valentin DE BORTOLI
CMLA
Adresse e-mail validée de cmla.ens-cachan.fr - Page d'accueil
Titre
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Année
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
82018
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
7*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
42019
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
22020
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
22020
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
22019
Convergence of diffusions and their discretizations: from continuous to discrete processes and back
V De Bortoli, A Durmus
arXiv preprint arXiv:1904.09808, 2019
22019
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
22019
Redundancy in Gaussian random fields
V De Bortoli, A Desolneux, B Galerne, A Leclaire
ESAIM: Probability and Statistics, 2018
22018
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
12020
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
12019
Maximum likelihood estimation of regularisation parameters in high-dimensional inverse problems: an empirical Bayesian approach. Part II: Theoretical Analysis
V De Bortoli, A Durmus, AF Vidal, M Pereyra
arXiv preprint arXiv:2008.05793, 2020
2020
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