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Publications associées (39)

Ce que les machines ont vu et que nous ne savons pas encore

Cet article conceptualise l’idée qu’il existe une « matière noire » composée des structurations latentes identifiées par le regard machinique sur de grandes collections photographiques patrimoniales. Les campagnes photographiques de l’histoire de l’art, au ...

2023

Learning Robust and Adaptive Representations: from Interactions, for Interactions

Yuejiang Liu

Interactions are ubiquitous in our world, spanning from social interactions between human individuals to physical interactions between robots and objects to mechanistic interactions among different components of an intelligent system. Despite their prevale ...

EPFL2023

Typicality results for weak solutions of the incompressible Navier-Stokes equations

Maria Colombo, Luigi De Rosa, Massimo Sorella

In this work we show that, in the class of L-infinity((0,T); L-2(T-3)) distributional solutions of the incompressible Navier-Stokes system, the ones which are smooth in some open interval of times are meagre in the sense of Baire category, and the Leray on ...

EDP SCIENCES S A2022

Localization errors of the stochastic heat equation

David Jean-Michel Candil

In this thesis, we study the stochastic heat equation (SHE) on bounded domains and on the whole Euclidean space

\R^d.

We confirm the intuition that as the bounded domain increases to the whole space, both solutions become arbitrarily close to one another ...

EPFL2022

Bootstrapping for Approximate Homomorphic Encryption with Negligible Failure-Probability by Using Sparse-Secret Encapsulation

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, Jean-Philippe Léonard Bossuat

Bootstrapping parameters for the approximate homomorphic-encryption scheme of Cheon et al., CKKS (Asiacrypt 17), are usually instantiated using sparse secrets to be efficient. However, using sparse secrets constrains the range of practical parameters withi ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

COMPUTATION OF "BEST" INTERPOLANTS IN THE L-p SENSE

Michaël Unser, Pakshal Narendra Bohra

We study a variant of the interpolation problem where the continuously defined solution is regularized by minimizing the L-p-norm of its second-order derivative. For this continuous-domain problem, we propose an exact discretization scheme that restricts t ...

IEEE2020

Path properties of the solution to the stochastic heat equation with Levy noise

Robert Dalang, Carsten Hao Ye Chong, Thomas Marie Jean-Baptiste Humeau

We consider sample path properties of the solution to the stochastic heat equation, in Rd or bounded domains of Rd, driven by a Levy space-time white noise. When viewed as a stochastic process in time with values in an infinite-dimensional space, the solut ...

SPRINGER2019

Characterization of local morphology and availability of triple-phase boundaries in solid oxide cell electrodes

Jan Van Herle, Marco Cantoni, Arata Nakajo, Pierre Burdet, Giorgio Rinaldi

The performance of solid oxide cells is known to be dependent upon the density of three phase boundaries (TPB), but the potential for improving their effective electrocatalytic activity by morphological adjustments is imprecisely known. A spilling algorith ...

2019

Modular Sensor Fusion for Semantic Segmentation

Roland Siegwart

Sensor fusion is a fundamental process in robotic systems as it extends the perceptual range and increases robustness in real-world operations. Current multi-sensor deep learning based semantic segmentation approaches do not provide robustness to under-per ...

2019

Shrinking Bouma's window: Visual crowding in dense displays

Michael Herzog, Gregory Francis, Adrien Christophe Doerig, Alban Bornet

In crowding, perception of a target deteriorates in the presence of nearby flankers. In the traditional feedforward framework of vision, only elements within Bouma’s window interfere with the target and adding more elements always leads to stronger crowdin ...

SAGE PUBLICATIONS LTD2019

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Localization errors of the stochastic heat equation

David Jean-Michel Candil

In this thesis, we study the stochastic heat equation (SHE) on bounded domains and on the whole Euclidean space

\R^d.

We confirm the intuition that as the bounded domain increases to the whole space, both solutions become arbitrarily close to one another ...

EPFL2022