no code implementations • 29 Feb 2024 • Barbara Pascal, Rémi Bardenet
The zeros of the spectrogram of a noisy signal are then the zeros of a random analytic function, hence forming a Point Process in $\mathbb{C}$.
1 code implementation • 17 Mar 2022 • Gersende Fort, Barbara Pascal, Patrice Abry, Nelly Pustelnik
The originality of the devised algorithms stems from combining a Langevin Monte Carlo sampling scheme with Proximal operators.
no code implementations • 11 Feb 2022 • Patrice Abry, Gersende Fort, Barbara Pascal, Nelly Pustelnik
Yet, the assessment of the pandemic intensity within the pandemic period remains a challenging task because of the limited quality of data made available by public health authorities (missing data, outliers and pseudoseasonalities, notably), that calls for cumbersome and ad-hoc preprocessing (denoising) prior to estimation.
1 code implementation • 8 Feb 2022 • Barbara Pascal, Rémi Bardenet
Recent work in time-frequency analysis proposed to switch the focus from the maxima of the spectrogram toward its zeros, which, for signals corrupted by Gaussian noise, form a random point pattern with a very stable structure leveraged by modern spatial statistics tools to perform component disentanglement and signal detection.
1 code implementation • 28 Sep 2021 • Charles-Gérard Lucas, Barbara Pascal, Nelly Pustelnik, Patrice Abry
This work focuses on a parameter-free joint piecewise smooth image denoising and contour detection.
no code implementations • 20 Sep 2021 • Barbara Pascal, Patrice Abry, Nelly Pustelnik, Stéphane G. Roux, Rémi Gribonval, Patrick Flandrin
The present work aims to overcome these limitations by carefully crafting a functional permitting to estimate jointly, in a single step, the reproduction number and outliers defined to model low quality data.
no code implementations • 20 Apr 2020 • Barbara Pascal, Samuel Vaiter, Nelly Pustelnik, Patrice Abry
This work extends the Stein's Unbiased GrAdient estimator of the Risk of Deledalle et al. to the case of correlated Gaussian noise, deriving a general automatic tuning of regularization parameters.