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Publications associées (28)

RG-Flow: a hierarchical and explainable flow model based on renormalization group and sparse prior

Dian Wu

Flow-based generative models have become an important class of unsupervised learning approaches. In this work, we incorporate the key ideas of renormalization group (RG) and sparse prior distribution to design a hierarchical flow-based generative model, RG ...

IOP Publishing Ltd2022

Filtered data and eigenfunction estimators for statistical inference of multiscale and interacting diffusion processes

Andrea Zanoni

We study the problem of learning unknown parameters of stochastic dynamical models from data. Often, these models are high dimensional and contain several scales and complex structures. One is then interested in obtaining a reduced, coarse-grained descript ...

EPFL2022

A Long Time Ago in a Galaxy Far, Far Away: A Candidate z similar to 12 Galaxy in Early JWST CEERS Imaging

Michaela Hirschmann

We report the discovery of a candidate galaxy with a photo -z of z similar to 12 in the first epoch of the James Webb Space Telescope (JWST) Cosmic Evolution Early Release Science Survey. Following conservative selection criteria, we identify a source with ...

IOP Publishing Ltd2022

Associations between urinary biomarkers of oxidative stress and biomarkers of tobacco smoke exposure in smokers

Florian Frédéric Vincent Breider, Dominique Grandjean

Oxidative stress can contribute to the development of diseases, and may originate from exposures to toxicants commonly found in air pollution and cigarette smoke such as polycyclic aromatic hydrocarbons (PAHs) and volatile organic compounds (VOCs). Yet, as ...

Elsevier2022

Novel trehalose-based excipients for stabilizing nebulized anti-SARS-CoV-2 antibody

Sandrine Gerber, Solène Marcelle Françoise Marie Passemard, François Rémi Pierre Noverraz

COVID-19 is caused by the infection of the lungs by SARS-CoV-2. Monoclonal antibodies, such as sotrovimab, showed great efficiency in neutralizing the virus before its internalization by lung epithelial cells. However, parenteral routes are still the prefe ...

2023

Bayesian Inversion for Nonlinear Imaging Models Using Deep Generative Priors

Michaël Unser, Thanh-An Michel Pham, Pakshal Narendra Bohra, Jonathan Yuelin Dong

Most modern imaging systems incorporate a computational pipeline to infer the image of interest from acquired measurements. The Bayesian approach to solve such ill-posed inverse problems involves the characterization of the posterior distribution of the im ...

2022

Improved framework to estimate travel time and derived distributions in hydrological control volumes

Mitra Asadollahi

Crossing properties of soil saturation, defined as the duration and excursion of soil saturation below and above certain thresholds, are key variables to ecosystem functioning and evolution by primarily influencing the plant and soil microbes physiological ...

EPFL2022

Using wavelets to capture deviations from smoothness in galaxy-scale strong lenses

Frédéric Courbin, Georgios Vernardos, Aymeric Alexandre Galan, Austin Chandler Peel

Modeling the mass distribution of galaxy-scale strong gravitational lenses is a task of increasing difficulty. The high-resolution and depth of imaging data now available render simple analytical forms ineffective at capturing lens structures spanning a la ...

EDP SCIENCES S A2022