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Publications associées (136)

PoGaIN: Poisson-Gaussian Image Noise Modeling From Paired Samples

Sabine Süsstrunk, Majed El Helou, Kaan Okumus

Image noise can often be accurately fitted to a Poisson-Gaussian distribution. However, estimating the distribution parameters from a noisy image only is a challenging task. Here, we study the case when paired noisy and noise-free samples are accessible. N ...

2022

Feature distribution learning by passive exposure

David Pascucci, Gizay Ceylan

Humans can rapidly estimate the statistical properties of groups of stimuli, including their average and variability. But recent studies of so-called Feature Distribution Learning (FDL) have shown that observers can quickly learn even more complex aspects ...

ELSEVIER2022

A Current Propagation Type Return Stroke Model Consistent with the Leader Charge Distribution

Marcos Rubinstein, Farhad Rachidi-Haeri

We describe a current propagation type return stroke model which is consistent with the estimated distribution of the charge on the leader channel. The model takes into account the dispersion of the return stroke current along the return stroke channel. Th ...

2021

Iron incorporation in synthetic precipitated calcium silicate hydrates

David Lyndon Emsley, Paul Bowen, Brennan James Walder, Jirawan Siramanont

Effect of Fe3+ on the precipitation of synthetic calcium silicate hydrates (C-S-H) under controlled conditions has been evaluated. Using extremely basic either initial calcium nitrate or sodium silicate solutions (pH > 11), incipient formation of ferrihydr ...

2021

Visualizing the multifractal wave functions of a disordered two-dimensional electron gas

Klaus Kern

The wave functions of a disordered two-dimensional electron gas at the quantum-critical Anderson transition are predicted to exhibit multifractal scaling in their real space amplitude. We experimentally investigate the appearance of these characteristics i ...

AMER PHYSICAL SOC2021

Large-Eddy Simulation of Wind Turbine Flows: A New Evaluation of Actuator Disk Models

Fernando Porté Agel, Tristan Revaz

Large-eddy simulation (LES) with actuator models has become the state-of-the-art numerical tool to study the complex interaction between the atmospheric boundary layer (ABL) and wind turbines. In this paper, a new evaluation of actuator disk models (ADMs) ...

2021

Hand pose selection in a bimanual fine-manipulation task

Aude Billard, Kunpeng Yao

Many daily tasks involve the collaboration of both hands. Humans dexterously adjust hand poses and modulate the forces exerted by fingers in response to task demands. Hand pose selection has been intensively studied in unimanual tasks, but little work has ...

2021

Robust discrete choice models with t-distributed kernel errors

Michel Bierlaire, Thomas Gasos, Prateek Bansal

Models that are robust to aberrant choice behaviour have received limited attention in discrete choice analysis. In this paper, we analyse two robust alternatives to the multinomial probit (MNP) model. Both alternative models belong to the family of robit ...

EPFL2020

Variational Inference with Mixture Model Approximation for Applications in Robotics

Sylvain Calinon, Emmanuel Pignat, Teguh Santoso Lembono

We propose to formulate the problem of repre-senting a distribution of robot configurations (e.g. joint angles)as that of approximating a product of experts. Our approach uses variational inference, a popular method in Bayesian computation, which has sever ...

2020

Distributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator

Daniel Kuhn, Viet Anh Nguyen, Peyman Mohajerin Esfahani

We introduce a distributionally robust maximum likelihood estimation model with a Wasserstein ambiguity set to infer the inverse covariance matrix of a p-dimensional Gaussian random vector from n independent samples. The proposed model minimizes the worst ...

2020

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