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Publications associées (9)

Counting using deep learning regression gives value to ecological surveys

Devis Tuia, Benjamin Alexander Kellenberger

Many ecological studies rely on count data and involve manual counting of objects of interest, which is time-consuming and especially disadvantageous when time in the field or lab is limited. However, an increasing number of works uses digital imagery, whi ...

2021

Quantifying the Effects of Contact Tracing, Testing, and Containment Measures in the Presence of Infection Hotspots

William Trouleau

Multiple lines of evidence at the individual and population level strongly suggest that infection hotspots, or superspreading events, where a single individual infects many others, play a key role in the transmission dynamics of COVID-19. However, most of ...

2020

Fragility Curves for Wide-Flange Steel Columns and Implications on Building-Specific Earthquake-Induced Loss Assessment

Dimitrios Lignos, Ahmed Mohamed Ahmed Elkady, Subash Ghimire

Building-specific loss assessment methodologies utilize component fragility curves to compute the expected losses in the aftermath of earthquakes. Such curves are not available for steel columns assuming they remain elastic due to capacity design considera ...

2018

Applications of Approximate Learning and Inference for Probabilistic Models

Young Jun Ko

We develop approximate inference and learning methods for facilitating the use of probabilistic modeling techniques motivated by applications in two different areas. First, we consider the ill-posed inverse problem of recovering an image from an underdeter ...

EPFL2017

Variational Gaussian Inference for Bilinear Models of Count Data

Mohammad Emtiyaz Khan, Young Jun Ko

Bilinear models of count data with Poisson distribution are popular in applications such as matrix factorization for recommendation systems, modeling of receptive fields of sensory neurons, and modeling of neural-spike trains. Bayesian inference in such mo ...

2014

Bits from Photons: Oversampled Image Acquisition Using Binary Poisson Statistics

Martin Vetterli, Luciano Sbaiz, Yue Lu, Feng Yang

We study a new image sensor that is reminiscent of traditional photographic film. Each pixel in the sensor has a binary response, giving only a one-bit quantized measurement of the local light intensity. To analyze its performance, we formulate the oversam ...

Institute of Electrical and Electronics Engineers2012

Comparison of Models for Olfactometer Data

Anthony Christopher Davison, Ingrid Ricard

Olfactometer experiments are used to study the responses of arthropods to potential attractants, for purposes such as understanding natural defenses of plants against their herbivores. Such experiments typically lead to multivariate data consisting of smal ...

Springer-Verlag2011

Bits from Photons: Oversampled Image Acquisition Using Binary Poisson Statistics

Martin Vetterli, Luciano Sbaiz, Yue Lu, Feng Yang

EPFL2011

Fast Interscale Wavelet Denoising of Poisson-Corrupted Images

Michaël Unser, Thierry Blu, Cédric René Jean Vonesch, Florian Luisier

We present a fast algorithm for image restoration in the presence of Poisson noise. Our approach is based on (1) the minimization of an unbiased estimate of the MSE for Poisson noise, (2) a linear parametrization of the denoising process and (3) the preser ...

Elsevier2010

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