Zobrazeno 1 - 10
of 770
pro vyhledávání: '"Abry, P."'
Publikováno v:
EUSIPCO, Aug 2024, Lyon, France
In numerous inverse problems, state-of-the-art solving strategies involve training neural networks from ground truth and associated measurement datasets that, however, may be expensive or impossible to collect. Recently, self-supervised learning tech
Externí odkaz:
http://arxiv.org/abs/2409.15283
In this paper, we characterize the convergence of the (rescaled logarithmic) empirical spectral distribution of wavelet random matrices. We assume a moderately high-dimensional framework where the sample size $n$, the dimension $p(n)$ and, for a fixe
Externí odkaz:
http://arxiv.org/abs/2401.02815
Self-supervised methods have recently proved to be nearly as effective as supervised methods in various imaging inverse problems, paving the way for learning-based methods in scientific and medical imaging applications where ground truth data is hard
Externí odkaz:
http://arxiv.org/abs/2312.11232
Scale-free dynamics, formalized by selfsimilarity, provides a versatile paradigm massively and ubiquitously used to model temporal dynamics in real-world data. However, its practical use has mostly remained univariate so far. By contrast, modern appl
Externí odkaz:
http://arxiv.org/abs/2311.03247
Understanding extreme events and their probability is key for the study of climate change impacts, risk assessment, adaptation, and the protection of living beings. Forecasting the occurrence probability of extreme heatwaves is a primary challenge fo
Externí odkaz:
http://arxiv.org/abs/2208.00971
Publikováno v:
IEEE Transactions on Signal Processing, In press
Monitoring the Covid19 pandemic constitutes a critical societal stake that received considerable research efforts. The intensity of the pandemic on a given territory is efficiently measured by the reproduction number, quantifying the rate of growth o
Externí odkaz:
http://arxiv.org/abs/2203.09142
Monitoring the evolution of the Covid19 pandemic constitutes a critical step in sanitary policy design. Yet, the assessment of the pandemic intensity within the pandemic period remains a challenging task because of the limited quality of data made av
Externí odkaz:
http://arxiv.org/abs/2202.05497
Publikováno v:
Signal, Image and Video Processing, 1-8 (2022)
This work focuses on a parameter-free joint piecewise smooth image denoising and contour detection. Formulated as the minimization of a discrete Mumford-Shah functional and estimated via a theoretically grounded alternating minimization scheme, the b
Externí odkaz:
http://arxiv.org/abs/2109.13651
Autor:
Pascal, Barbara, Abry, Patrice, Pustelnik, Nelly, Roux, Stéphane G., Gribonval, Rémi, Flandrin, Patrick
Daily pandemic surveillance, often achieved through the estimation of the reproduction number, constitutes a critical challenge for national health authorities to design countermeasures. In an earlier work, we proposed to formulate the estimation of
Externí odkaz:
http://arxiv.org/abs/2109.09595
In this paper, we construct the wavelet eigenvalue regression methodology in high dimensions. We assume that possibly non-Gaussian, finite-variance $p$-variate measurements are made of a low-dimensional $r$-variate ($r \ll p$) fractional stochastic p
Externí odkaz:
http://arxiv.org/abs/2108.03770