Publications associées à Hire Me: Computational inference of hirability in employment interviews based on nonverbal behavior

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo theory of linear response and Bayesian regression analysis. By exploiting the ...

Amer Chemical Soc2024

Random matrix methods for high-dimensional machine learning models

Antoine Philippe Michel Bodin

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

EPFL2024

Iterative removal of sources to model the turbulent electromotive force

Jennifer Waltraud Schober, Abhijit Bhausaheb Bendre

We describe a novel method to compute the components of dynamo tensors from direct magnetohydrodynamic (MHD) simulations. Our method relies upon an extension and generalization of the standard H & ouml;gbom CLEAN algorithm widely used in radio astronomy to ...

Oxford Univ Press2024

On distributional autoregression and iterated transportation

Victor Panaretos, Laya Ghodrati

We consider the problem of defining and fitting models of autoregressive time series of probability distributions on a compact interval of Double-struck capital R. An order-1 autoregressive model in this context is to be understood as a Markov chain, where ...

Wiley2024

Model reduction of coupled systems based on non-intrusive approximations of the boundary response maps

Jan Sickmann Hesthaven, Niccolo' Discacciati

We propose a local, non -intrusive model order reduction technique to accurately approximate the solution of coupled multi -component parametrized systems governed by partial differential equations. Our approach is based on the approximation of the boundar ...

Elsevier Science Sa2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Secure and Efficient Cryptographic Algorithms in a Quantum World

Loïs Evan Huguenin-Dumittan

Since the advent of internet and mass communication, two public-key cryptographic algorithms have shared the monopoly of data encryption and authentication: Diffie-Hellman and RSA. However, in the last few years, progress made in quantum physics -- and mo ...

EPFL2024

Dynamic Voxels Based on Ego-Conditioned Prediction: An Integrated Spatio-Temporal Framework for Motion Planning

Alexandre Massoud Alahi, Ting Zhang

Prediction is a vital component of motion planning for autonomous vehicles (AVs). By reasoning about the possible behavior of other target agents, the ego vehicle (EV) can navigate safely, efficiently, and politely. However, most of the existing work overl ...

IEEE Institute of Electrical and Electronics Engineers2024

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

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

Comparison of questionnaire items for discomfort glare studies in daylit spaces

Marilyne Andersen, Jan Wienold, Clotilde Marie A Pierson, Geraldine Cai Ting Quek, Sneha Jain, Caroline Karmann

When studying discomfort glare, researchers tend to rely on a single questionnaire item to obtain user evaluations. It is unclear whether the choice of questionnaire item affects the distribution of user responses and leads to inconsistencies between studi ...

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

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

Hugo Chao Cui, Florent Gérard Krzakala, Lenka Zdeborová

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

Untangling the influence of Antarctic and Southern Ocean life on clouds

Jenny Thomas, Julia Schmale, Hélène Paule Angot, Markus Frey

Polar environments are among the fastest changing regions on the planet. It is a crucial time to make significant improvements in our understanding of how ocean and ice biogeochemical processes are linked with the atmosphere. This is especially true over A ...

2023

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

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

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

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

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

Devis Tuia, Oleg Antropov, Sudipan Saha, 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

Quality-Constrained Encoding Optimization for Omnidirectional Video Streaming

Pascal Frossard, Roberto Gerson De Albuquerque Azevedo, Chaofan He

Omnidirectional video streaming is usually implemented based on the representations of tiles, where the tiles are obtained by splitting the video frame into several rectangular areas and each tile is converted into multiple representations with different r ...

Ieee-Inst Electrical Electronics Engineers Inc2023

Predicting Survey Response with Quotation-based Modeling: A Case Study on Favorability towards the United States

Saleh Baghersalimi, Jonathan Philippe Reymond, Alireza Amirshahi

The acquisition of survey responses is a crucial component in conducting research aimed at comprehending public opinion. However, survey data collection can be arduous, time-consuming, and expensive, with no assurance of an adequate response rate. In this ...

IEEE COMPUTER SOC2023

Creating the conditions for Western European petroculture: The Marshall Plan, the politics of the OEEC, and the transition from coal to oil

Nicolas Christophe Chachereau

In the postwar years, petroleum products pervaded more and more aspects of Western European life. In this article, we study the origins of this pervasive petroculture through the lens of the Marshall Plan/European Recovery Program (ERP), its Refinery Expan ...

2023

On the Validity of Consensus

Rachid Guerraoui, Seth Gilbert, Manuel José Ribeiro Vidigueira, Jovan Komatovic, Pierre Philippe Civit

The Byzantine consensus problem involves.. processes, out of which t < n could be faulty and behave arbitrarily. Three properties characterize consensus: (1) termination, requiring correct (nonfaulty) processes to eventually reach a decision, (2) agreement ...

Assoc Computing Machinery2023