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Estimating the non-linear dynamics of free-flying objects

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Publications associées (41)

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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

Stability: a search for structure

Wouter Jongeneel

In this thesis we study stability from several viewpoints. After covering the practical importance, the rich history and the ever-growing list of manifestations of stability, we study the following. (i) (Statistical identification of stable dynamical syste ...

EPFL2024

Efficient local linearity regularization to overcome catastrophic overfitting

Volkan Cevher, Grigorios Chrysos, Fanghui Liu, Elias Abad Rocamora

Catastrophic overfitting (CO) in single-step adversarial training (AT) results in abrupt drops in the adversarial test accuracy (even down to 0%). For models trained with multi-step AT, it has been observed that the loss function behaves locally linearly w ...

2024

Diverse parameters of ambulatory knee moments differ with medial knee osteoarthritis severity and are combinable into a severity index

Julien Favre, Brigitte Jolles-Haeberli

Objective: To characterize ambulatory knee moments with respect to medial knee osteoarthritis (OA) severity comprehensively and to assess the possibility of developing a severity index combining knee moment parameters. ...

FRONTIERS MEDIA SA2023

Test-time adaptation for 6D pose tracking

Andrea Cavallaro

We propose a test -time adaptation for 6D object pose tracking that learns to adapt a pre -trained model to track the 6D pose of novel objects. We consider the problem of 6D object pose tracking as a 3D keypoint detection and matching task and present a mo ...

Elsevier Sci Ltd2024

Adequacy of stationary measurements as proxies for residential personal exposure to gaseous and particle air pollutants

Dusan Licina, Maria Viviana Gonzalez Serrano

People are exposed to myriad of airborne pollutants in their homes. Owing to diverse potential sources of air pollution and human activity patterns, accurate assessment of residential exposures is complex. In this study, we explored the relationship betwee ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Beyond the average consumer: Mapping the potential of demand-side management among patterns of appliance usage

Selin Yilmaz, Claudia Rebeca Binder Signer, Matteo Barsanti

To support the decarbonisation of the power sector and offset the volatility of a system with high levels of renewables, there is growing interest in residential Demand-Side Management (DSM) solutions. Traditional DSM strategies require consumers to active ...

2024

Spatial Distributions of Diarrheal Cases in Relation to Housing Conditions in Informal Settlements: A Cross-Sectional Study in Abidjan, Côte d’Ivoire

Jérôme Chenal, Vitor Pessoa Colombo, Jürg Utzinger

In addition to individual practices and access to water, sanitation, and hygiene (WASH) facilities, housing conditions may also be associated with the risk of diarrhea. Our study embraced a broad approach to health determinants by looking at housing depriv ...

2023

Sequential CNN-based Enhancement of Ultrafast Ultrasound Imaging for Sparse Arrays

Jean-Philippe Thiran, Roser Vinals Terres

With the emergence of ultra-portable ultrasound systems, the need to reduce cost and complexity of ultrasound systems has intensified. Sparse arrays, employing fewer transducer elements to acquire images, offer a viable solution by effectively minimizing d ...

European Signal Processing Conference, EUSIPCO2024

Acute TNF alpha levels predict cognitive impairment 6-9 months after COVID-19 infection

Dimitri Nestor Alice Van De Ville, Alessandra Griffa, Idris Guessous, Alexandre Cionca

Background: A neurocognitive phenotype of post-COVID-19 infection has recently been described that is characterized by a lack of awareness of memory impairment (i.e., anosognosia), altered functional connectivity in the brain's default mode and limbic netw ...

PERGAMON-ELSEVIER SCIENCE LTD2023

DARE-GRAM : Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matrices

Olga Fink, Ismail Nejjar

Unsupervised Domain Adaptation Regression (DAR) aims to bridge the domain gap between a labeled source dataset and an unlabelled target dataset for regression problems. Recent works mostly focus on learning a deep feature encoder by minimizing the discrepa ...

IEEE2023

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Lenka Zdeborová, Florent Gérard Krzakala, Hugo Chao Cui

We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

2023

Semi-Supervised Deep Learning Representations in Earth Observation Based Forest Management

Devis Tuia, Marc Conrad Russwurm, Lloyd Haydn Hughes

In this study, we examine the potential of several self-supervised deep learning models in predicting forest attributes and detecting forest changes using ESA Sentinel-1 and Sentinel-2 images. The performance of the proposed deep learning models is compare ...

The Institute of Electrical and Electronics Engineers, Inc2023

Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial

Olga Fink, Luca Biggio

On top of machine learning (ML) models, uncertainty quantification (UQ) functions as an essential layer of safety assurance that could lead to more principled decision making by enabling sound risk assessment and management. The safety and reliability impr ...

2023

Distributional Regression and Autoregression via Optimal Transport

Laya Ghodrati

We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of

\R^d

. Our regression model is based on the theory of optimal transport and links the conditional Fr'echet m ...

EPFL2023

(S)GD over Diagonal Linear Networks: Implicit Regularisation, Large Stepsizes and Edge of Stability

Nicolas Henri Bernard Flammarion, Scott William Pesme

In this paper, we investigate the impact of stochasticity and large stepsizes on the implicit regularisation of gradient descent (GD) and stochastic gradient descent (SGD) over diagonal linear networks. We prove the convergence of GD and SGD with macroscop ...

2023

Reliable uncertainties: Error correlation, rotated error bars, and linear regressions in three-isotope plots and beyond

Reto Georg Trappitsch

Correlated errors of experimental data are a common but often neglected problem in physical sciences. Various tools are provided here for thorough propagation of uncertainties in cases of correlated errors. Discussed are techniques especially applicable to ...

ELSEVIER2023

Analysing the potential for modal shiftbased on the logic of modal choice

Vincent Kaufmann, Ludy Juliana González Villamizar, Eloi Antoine Maël Bernier, Florian Lucien Jacques Masse

This article explores how the logic underlying modal practices tends to modulate the population’s responsiveness to improvements in global transport supply. Based on a quantitative survey conducted in 2018–2019 among the working population of the cantons o ...

2023

Linear Recursive State Estimation of Hybrid and Unbalanced AC/DC Micro-Grids using Synchronized Measurements

Mario Paolone, Willem Lambrichts

In this paper, we present an exact (i. e. non-approximated) and linear measurement model for hybrid AC/DC microgrids for recursive state estimation (SE). More specifically, an exact linear model of a voltage source converter (VSC) is proposed. It relies on ...

New York2023

Climatic and Economic Background Determine the Disparities in Urbanites’ Expressed Happiness during the Summer Heat

Gabriele Manoli

Climate-change-induced extreme weather events increase heat-related mortality and health risks for urbanites, which may also affect urbanites’ expressed happiness (EH) and well-being. However, the links among EH, climate, and socioeconomic factors remain u ...

2023