Extended precision

Formal sciences
Mathematics
Analysis
Numerical analysis

About
Privacy
Disclaimer

Graph Chatbot

Related publications (31)

Monitoring weekly progress of front crawl swimmers using IMU-based performance evaluation goal metrics

Kamiar Aminian, Farzin Dadashi, Fabien Massé, Mahdi Hamidi Rad, Vincent Gremeaux

Technical evaluation of swimming performance is an essential factor in preparing elite swimmers for their competitions. Inertial measurement units (IMUs) have attracted much attention recently because they can provide coaches with a detailed analysis of sw ...

FRONTIERS MEDIA SA2022

A platform for experimental precision medicine: The extended BXD mouse family

Johan Auwerx, Evan Graehl Williams

The challenge of precision medicine is to model complex interactions among DNA variants, phenotypes, development, environments, and treatments. We address this challenge by expanding the BXD family of mice to 140 fully isogenic strains, creating a uniquely ...

CELL PRESS2021

Une approche computationnelle du cadastre napoléonien de Venise

Frédéric Kaplan, Isabella Di Lenardo, Raphaël Barman, Federica Pardini

At the beginning of the 19th century, the Napoleonic administration introduced a new standardised description system to give an objective account of the form and functions of the city of Venice. The cadastre, deployed on a European scale, was offering for ...

2021

Development and evaluation of galaxy shape measurement algorithms for radio interferometric data

Vasileios Angelopoulos

The purpose of this Thesis is to develop, test, and characterize different models attempting to tackle the problem of measurement of galaxy shapes applied in interferometric observations. Shape measurement is a tool for estimating the underlying shear due ...

EPFL2021

Self-Supervised Pretraining and Controlled Augmentation Improve Rare Wildlife Recognition in UAV Images

Devis Tuia, Benjamin Alexander Kellenberger, Xiaochen Zheng, Rui Gong

Automated animal censuses with aerial imagery are a vital ingredient towards wildlife conservation. Recent models are generally based on deep learning and thus require vast amounts of training data. Due to their scarcity and minuscule size, annotating anim ...

IEEE2021

The structural connectome and motor recovery after stroke: predicting natural recovery

Jean-Philippe Thiran, Friedhelm Christoph Hummel, Gabriel Girard, Takuya Morishita, Elena Beanato, Maximilian Jonas Wessel, Chang-Hyun Park, Philipp Johannes Koch, Philip Egger, Giorgia Giulia Evangelista

Stroke patients vary considerably in terms of outcomes: some patients present ‘natural’ recovery proportional to their initial impairment (fitters), while others do not (non-fitters). Thus, a key challenge in stroke rehabilitation is to identify individual ...

2021

High Performance Computing for gravitational lens modeling: Single vs double precision on GPUs and CPUs

Jean-Paul Richard Kneib, Markus Rexroth, Christoph Ernst René Schäfer

Strong gravitational lensing is a powerful probe of cosmology and the dark matter distribution. Efficient lensing software is already a necessity to fully use its potential and the performance demands will only increase with the upcoming generation of tele ...

ELSEVIER2020

Mixed-Precision Deep Learning Based on Computational Memory

Irem Boybat Kara, Evangelos Eleftheriou, Abu Sebastian

Deep neural networks (DNNs) have revolutionized the field of artificial intelligence and have achieved unprecedented success in cognitive tasks such as image and speech recognition. Training of large DNNs, however, is computationally intensive and this has ...

FRONTIERS MEDIA SA2020

Smooth Power Direction Transition of a Bidirectional LLC Resonant Converter for DC Transformer Applications

Drazen Dujic, Jakub Kucka

The bidirectional LLC resonant converter operated at fixed switching frequency is a preferable candidate for a true dc transformer that does not actively control the power flow. This is due to its naturally stiff voltage ratio regardless of the imposed loa ...

2020

ColTraIn: Co-located DNN training and inference

Mario Paulo Drumond Lages De Oliveira

Deep neural network inference accelerators are deployed at scale to accommodate online services, but face low average load because of service demand variability, leading to poor resource utilization. Unfortunately, reclaiming inference idle cycles is diffi ...

EPFL2020

High Precision Capacitive Moisture Sensor for Polymers: Modeling and Experiments

Marco Mattavelli, Jean-Michel Sallese, Catherine Dehollain, Diego Ruben Barrettino

In this work a high precision capacitive moisture sensor for polymers was designed and fabricated. The device is part of a compact, fast, and economic moisture analyzer capable of reaching a similar precision than commercial moisture analyzers based on the ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Page 2 of 2