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Publications associées (1 000)

Residual-based attention in physics-informed neural networks

Nikolaos Stergiopoulos, Sokratis Anagnostopoulos

Driven by the need for more efficient and seamless integration of physical models and data, physics -informed neural networks (PINNs) have seen a surge of interest in recent years. However, ensuring the reliability of their convergence and accuracy remains ...

Lausanne2024

Mapping Bibliotheca Hertziana

Hannah Laureen Casey

The project introduces an innovative visual method for analysing libraries and archives, with a focus on Bibliotheca Hertziana’s library collection. This collection, which dates back over a century, is examined by integrating user loan data with deep mappi ...

2024

Domain adaptation via alignment of operation profile for Remaining Useful Lifetime prediction

Olga Fink, Ismail Nejjar, Mengjie Zhao

Effective Prognostics and Health Management (PHM) relies on accurate prediction of the Remaining Useful Life (RUL). Data-driven RUL prediction techniques rely heavily on the representativeness of the available time-to-failure trajectories. Therefore, these ...

2024

General and Unified Model of the Power Flow Problem in Multiterminal AC/DC Networks

Mario Paolone, Willem Lambrichts

This paper proposes a generic and unified model of the power flow (PF) problem for multiterminal hybrid AC/DC networks. The proposed model is an extension of the standard AC-PF. The DC network is treated as an AC one and, in addition to the Slack, PV and P ...

2024

Robust Data-Driven Controller Design with Finite Frequency Samples

Alireza Karimi, Philippe Louis Schuchert

Modern control synthesis methods rely on accurate models to derive a performant controller. Obtaining a good model is often a costly step, and has led to a renewed interest in data-driven synthesis methods. Frequency-response-based synthesis methods have b ...

2024

Energy-Efficient Frequency Selection Method for Bio-Signal Acquisition in AI/ML Wearables

David Atienza Alonso, Miguel Peon Quiros, José Angel Miranda Calero, Hossein Taji

In wearable sensors, energy efficiency is crucial, particularly during phases where devices are not processing, but rather acquiring biosignals for subsequent analysis. This study focuses on improving the power consumption of wearables during these acquisi ...

2024

Euclid: Improving the efficiency of weak lensing shear bias calibration

Frédéric Courbin, Georges Meylan, Malte Tewes, Yi Wang, Richard Massey, Marcello Farina

To obtain an accurate cosmological inference from upcoming weak lensing surveys such as the one conducted by Euclid, the shear measurement requires calibration using galaxy image simulations. As it typically requires millions of simulated galaxy images and ...

Edp Sciences S A2024

Inverse Problems in Pulse-Echo Ultrasound: Exploiting Coherence for Image Enhancement and Quantitative Imaging

Samuel Denys Beuret

Whereas pulse-echo ultrasound imaging relied on focused acoustic waves since its inception, the last two decades have seen the development of techniques based on unfocused waves, including ultrafast ultrasound imaging. In large part due to the emergence of ...

EPFL2024

Machine learning method for the classification of the state of living organisms' oscillations

Sandor Kasas, María Inés Villalba

The World Health Organization highlights the urgent need to address the global threat posed by antibiotic-resistant bacteria. Efficient and rapid detection of bacterial response to antibiotics and their virulence state is crucial for the effective treatmen ...

Frontiers Media Sa2024

Impact of beam-beam effects on absolute luminosity calibrations at the CERN Large Hadron Collider

Tatiana Pieloni, Claudia Tambasco

At the Large Hadron Collider (LHC), absolute luminosity calibrations obtained by the van der Meer (vdM) method are affected by the mutual electromagnetic interaction of the two beams. The colliding bunches experience relative orbit shifts, as well as optic ...

New York2024

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