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Concept

Exactitude et précision

Publications associées (29)

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Olga Fink, Hao Lu

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

2024

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Jean-Paul Richard Kneib, Emma Elizabeth Tolley, Michele Bianco, Tianyue Chen

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Oxford Univ Press2024

Design of an Open-Loop Pile-Oscillation Program in the CROCUS Reactor

Andreas Pautz, Vincent Pierre Lamirand, Axel Guy Marie Laureau, Thomas Jean-François Ligonnet

As a follow-up to the CEA-EPFL PETALE experimental program on stainless steel nuclear data, the EPFL initiated an open-loop pile-oscillation experimental program in the CROCUS reactor: BLOOM. A reproduction of the critical experiments of PETALE, the progra ...

2024

CURLING - I. The influence of point-like image approximation on the outcomes of cluster strong lens modelling

Jean-Paul Richard Kneib, Huanyuan Shan, Nan Li

Cluster-scale strong lensing is a powerful tool for exploring the properties of dark matter and constraining cosmological models. However, due to the complex parameter space, pixelized strong lens modelling in galaxy clusters is computationally expensive, ...

Oxford Univ Press2024

Capsizing due to friction-induced twist in the failure of stopper knots

Pedro Miguel Nunes Pereira de Almeida Reis, Paul Johanns

We investigate the failure mechanism of stopper knots, with a particular focus on the figure -8 knot as a representative example. Stopper knots are widely used in climbing, sailing, racket stringing, and sewing to maintain tension in ropes, strings, or thr ...

Elsevier2024

Towards Robust Monitoring of the Laser Powder Bed Fusion Process based on Acoustic Emission combined with Machine Learning Solutions

Rita Drissi Daoudi

Laser Powder Bed Fusion (LPBF) is an Additive Manufacturing (AM) process consolidating parts layer by layer, from a metallic powder bed. It allows no limitation in terms of geometry and is therefore of particular interest to various industries. Metallic LP ...

EPFL2023

On double-descent in uncertainty quantification in overparametrized models

Lenka Zdeborová, Florent Gérard Krzakala, Bruno Loureiro, Lucas Andry Clarte

Uncertainty quantification is a central challenge in reliable and trustworthy machine learning. Naive measures such as last-layer scores are well-known to yield overconfident estimates in the context of overparametrized neural networks. Several methods, ra ...

PMLR Proceedings of Machine Learning Research2023

Revisiting adversarial training for the worst-performing class

Volkan Cevher, Grigorios Chrysos, Thomas Michaelsen Pethick

Despite progress in adversarial training (AT), there is a substantial gap between the topperforming and worst-performing classes in many datasets. For example, on CIFAR10, the accuracies for the best and worst classes are 74% and 23%, respectively. We argu ...

Journal of Machine Learning Research Inc.2023

Accurate Measurement of Dynamic ON-Resistance in GaN Transistors at Steady-State

Elison de Nazareth Matioli, Hongkeng Zhu

Accurate characterization of the dynamic ON-resistance (RON) degradation is important to predict conduction losses for gallium nitride high-electron-mobility transistors (GaN HEMTs). However, even for the same device, many inconsistent results of dynamic R ...

2023

Automatic and high-precision acoustic emission-based structural health monitoring of concrete structures

Brice Tanguy Alphonse Lecampion, Seyyedmaalek Momeni

Acoustic emission (AE) monitoring is a useful technique to monitor the health of a structure continuously, helping to prevent potential failure. AE are elastic waves produced and emitted during fracture processes inside a material and are recorded by senso ...

DESTech publications inc.2023

BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

Pascal Fua, Sean Lewis Hill, Jiancheng Yang, Amos Sironi, Jian Yang

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in m ...

Nature Publishing Group2023

Observation of the Rare Decay of the η Meson to Four Muons

Jian Wang, Matthias Finger, Qian Wang, Yiming Li, João Miguel das Neves Duarte, Matthias Wolf, Varun Sharma, Yi Zhang, Tian Cheng, Yixing Chen, Alexis Kalogeropoulos, Ioannis Papadopoulos, Hua Zhang, Siyuan Wang, Xin Chen, Michele Bianco, Sebastiana Gianì, Sun Hee Kim, Rakesh Chawla, Jan Steggemann, Konstantin Androsov, Anna Mascellani, Federica Legger, Matteo Galli, Gabriele Grosso

A search for the rare eta -> mu(+)mu(-)mu(+)mu(-) double-Dalitz decay is performed using a sample of proton-proton collisions, collected by the CMS experiment at the CERN LHC with high-rate muon triggers during 2017 and 2018 and corresponding to an integra ...

Amer Physical Soc2023

Epidemic Learning: Boosting Decentralized Learning with Randomized Communication

Rachid Guerraoui, Anne-Marie Kermarrec, Rafael Pereira Pires, Rishi Sharma, Marinus Abraham de Vos, Sadegh Farhadkhani

We present Epidemic Learning ( EL ), a simple yet powerful decentralized learning (DL) algorithm that leverages changing communication topologies to achieve faster model convergence compared to conventional DL approaches. At each round of EL, each node sen ...

2023

Divide-and-conquer one-step simulator for the generation of synthetic households

Michel Bierlaire, Marija Kukic

This paper presents a novel simulation approach for generating synthetic households, addressing several literature gaps from the methodological viewpoint. The generation of hierarchical datasets such as complete households is challenging since it must guar ...

2023

Euclid preparation: XXVIII. Forecasts for ten different higher-order weak lensing statistics

Maurizio Martinelli, Frédéric Courbin, Gianluca Castignani, Austin Chandler Peel

Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale ...

EDP SCIENCES S A2023

High-precision optical magnetometry using Nitrogen Vacancies in CVD diamond

Hossein Babashah

Sensing weak magnetic fields is a topic of great importance in basic science and technology due to its wide range of applications. In this context, solid-state and nanoscale quantum sensors are poised to revolutionize the sensing platforms due to their ult ...

EPFL2023

Efficient and Accurate Peer-to-Peer Training of Machine Learning Based Home Thermal Models

Rachid Guerraoui, Alexandre David Olivier Maurer

The integration of smart thermostats in home automation systems has created an opportunity to optimize space heating and cooling through the use of machine learning, for example for thermal model identification. Nonetheless, its full potential remains unta ...

Assoc Computing Machinery2023

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Soumaya Elkantassi

Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. ...

EPFL2023

High-affinity peptides developed against calprotectin and their application as synthetic ligands in diagnostic assays

Christian Heinis, Florence Pojer, Kelvin Ka Ching Lau, Cristina Diaz Perlas, Lluc Farrera Soler

A peptide was developed that binds to calprotectin, a marker of major inflammatory disorders, and found to be suited for diagnostic tests. The use of synthetic peptides in assays is of great interest due to their high precision, robustness and low price. ...

Nature Portfolio2023

Mixed-precision explicit stabilized Runge-Kutta methods for single- and multi-scale differential equations

Giacomo Rosilho De Souza

Mixed-precision algorithms combine low-and high-precision computations in order to benefit from the performance gains of reduced-precision without sacrificing accuracy. In this work, we design mixed-precision Runge-Kutta-Chebyshev (RKC) methods, where high ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

Publications associées (29)

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Olga Fink, Hao Lu

2024

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Jean-Paul Richard Kneib, Emma Elizabeth Tolley, Michele Bianco, Tianyue Chen

Oxford Univ Press2024

Towards Robust Monitoring of the Laser Powder Bed Fusion Process based on Acoustic Emission combined with Machine Learning Solutions

Rita Drissi Daoudi

EPFL2023

BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

Pascal Fua, Sean Lewis Hill, Jiancheng Yang, Amos Sironi, Jian Yang

Nature Publishing Group2023