Concept

Accuracy and precision

Related publications (409)

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Accurate and agile flight with winged drones

Valentin Wüest

Drones hold promise to assist in civilian tasks. To realize this application, future drones must operate within large cities, covering large distances while navigating within cluttered urban landscapes. The increased efficiency of winged drones over rotary ...

EPFL2024

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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

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

Muon Collider Forum report

João Miguel das Neves Duarte, Andrea Wulzer, Théodora Cohen Liechti, Wei Li, Xiao Wang, Christoph Herwig

A multi-TeV muon collider offers a spectacular opportunity in the direct exploration of the energy frontier. Offering a combination of unprecedented energy collisions in a comparatively clean leptonic environment, a high energy muon collider has the unique ...

Iop Publishing Ltd2024

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

Surrogate deep neural networks (DNNs) can significantly speed up the engineering design process by providing a quick prediction that emulates simulated data. Many previous works have considered improving the accuracy of such models by introducing additiona ...

2023

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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 ...

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

Epidemic Learning: Boosting Decentralized Learning with Randomized Communication

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

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