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Topology classification with deep learning to improve real-time event selection at the LHC

Publications associées (51)

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Center-aware Adversarial Augmentation for Single Domain Generalization

Mathieu Salzmann, Zhiye Wang

Domain generalization (DG) aims to learn a model from multiple training (i.e., source) domains that can generalize well to the unseen test (i.e., target) data coming from a different distribution. Single domain generalization (SingleDG) has recently emerge ...

IEEE COMPUTER SOC2023

Data-driven and model-driven methodologies can be regarded as competitive fields since they tackle similar problems such as prediction. However, these two fields can learn from each other to improve themselves. Indeed, data-driven methodologies have been d ...

EPFL2022

Robustness Analysis of Metasurfaces: Perfect Structures Are Not Always the Best

Olivier Martin, Karim Achouri, Hsiang-Chu Wang

Optical metasurfaces rely on subwavelength scale nanostructures, which puts significant constraints on nanofabrication accuracies. These constraints are becoming increasingly important, as metasurfaces are maturing toward real applications that require the ...

AMER CHEMICAL SOC2022

Development of microdevices for the in-plane thermoelectric characterization of deposited films

Stefano Mischler

Measuring the thermoelectric transport properties of a material is a prerequisite to determining its usefulness for application in waste heat recovery or cooling and the basis for devising improvement strategies. While well-established characterization met ...

ELSEVIER2021

The role of demand in fostering product vs process innovation: a model and an empirical test

Gabriele Pellegrino

While the extant innovation literature has provided extensive evidence of the so-called "demand-pull" effect, the possible diverse impact of demand evolution on product vs process innovation activities has not been yet investigated. This paper develops a f ...

SPRINGER2020

This study evaluates mechanisms of biogenic mineral formation induced by bacterial iron reduction for the stabilization of corroded iron. As an example, the Desulfitobacterium hafniense strain TCE1 was employed to treat corroded coupons presenting urban na ...

2020

Rethinking Sampling in Parallel MRI: A Data-Driven Approach

Volkan Cevher, Baran Gözcü, Thomas Sanchez

In the last decade, Compressive Sensing (CS) has emerged as the most promising, model-driven approach to accelerate MRI scans. CS relies on the key sparsity assumption and proposes random sampling for data acquisition. The practical CS approaches in MRI em ...

IEEE2019

Retroactive Packet Sampling for Traffic Receipts

Pavlos Nikolopoulos, Adrian Perrig, Christos Pappas

Is it possible to design a packet-sampling algorithm that prevents the network node that performs the sampling from treating the sampled packets preferentially? We study this problem in the context of designing a "network transparency" system. In this syst ...

ACM2019

Sampling at unknown locations, with an application in surface retrieval

Martin Vetterli, Benjamin Bejar Haro, Adam James Scholefield, Michalina Wanda Pacholska

We consider the problem of sampling at unknown locations. We prove that, in this setting, if we take arbitrarily many samples of a polynomial or real bandlimited signal, it is possible to find another function in the same class, arbitrarily far away from t ...

2017

Optimization of SEM-EDS to determine the C-A-S-H composition in matured cement paste samples

Karen Scrivener, John Espen Rossen

Microanalysis of characteristic X-rays in the SEM is a powerful method to assess the chemical composition of phases in cement pastes, in particular the calcium silicate hydrate containing aluminium (C-A-S-H). Nevertheless, many variables may influence the ...

Elsevier Science Inc2017