Search Results for author: Julie Delon

Found 9 papers, 4 papers with code

Can Push-forward Generative Models Fit Multimodal Distributions?

no code implementations29 Jun 2022 Antoine Salmona, Valentin De Bortoli, Julie Delon, Agnès Desolneux

More precisely, we show that the total variation distance and the Kullback-Leibler divergence between the generated and the data distribution are bounded from below by a constant depending on the mode separation and the Lipschitz constant.

On Maximum-a-Posteriori estimation with Plug & Play priors and stochastic gradient descent

no code implementations16 Jan 2022 Rémi Laumont, Valentin De Bortoli, Andrés Almansa, Julie Delon, Alain Durmus, Marcelo Pereyra

Bayesian methods to solve imaging inverse problems usually combine an explicit data likelihood function with a prior distribution that explicitly models expected properties of the solution.

Image Denoising

Wasserstein Distances, Geodesics and Barycenters of Merge Trees

1 code implementation16 Jul 2021 Mathieu Pont, Jules Vidal, Julie Delon, Julien Tierny

We extend recent work on the edit distance [106] and introduce a new metric, called the Wasserstein distance between merge trees, which is purposely designed to enable efficient computations of geodesics and barycenters.

Bayesian imaging using Plug & Play priors: when Langevin meets Tweedie

no code implementations8 Mar 2021 Rémi Laumont, Valentin De Bortoli, Andrés Almansa, Julie Delon, Alain Durmus, Marcelo Pereyra

The proposed algorithms are demonstrated on several canonical problems such as image deblurring, inpainting, and denoising, where they are used for point estimation as well as for uncertainty visualisation and quantification.

Bayesian Inference Deblurring +2

DVDnet: A Fast Network for Deep Video Denoising

1 code implementation4 Jun 2019 Matias Tassano, Julie Delon, Thomas Veit

Previous neural network based approaches to video denoising have been unsuccessful as their performance cannot compete with the performance of patch-based methods.

Denoising Video Denoising

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