Publications associées à Model misspecification in peaks over threshold analysis

Publications associées (31)

Functional-Basis Analysis of Non-Stationary Signals in Modern Power Grids: Theory and Implementation in Embedded Systems

Situational awareness strategies are essential for the reliable and secure operation of the electric power grid which represents critical infrastructure in modern society. With the rise of converter-interfaced renewable generation and the consequent shift ...

EPFL2024

Extensions of Peer Prediction Incentive Mechanisms

Adam Julian Richardson

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

EPFL2024

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

Paolo Pegolo

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

Spectral Estimators for High-Dimensional Matrix Inference

Farzad Pourkamali

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024

Graph generative deep learning models with an application to circuit topologies

Igor Krawczuk

Modern integrated circuits are tiny yet incredibly complex technological artifacts, composed of millions and billions of individual structures working in unison. Managing their complexity and facilitating their design drove part of the co-evolution of mode ...

EPFL2024

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Pakshal Narendra Bohra

In inverse problems, the task is to reconstruct an unknown signal from its possibly noise-corrupted measurements. Penalized-likelihood-based estimation and Bayesian estimation are two powerful statistical paradigms for the resolution of such problems. They ...

EPFL2024

Identification of typical district configurations: A two-step global sensitivity analysis framework

François Maréchal, Jonas Schnidrig, Cédric Terrier, Arthur Antoine Chuat

The recent geopolitical conflicts in Europe have underscored the vulnerability of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy systems ensuring sustainable energy supply in the future, the ...

Pergamon-Elsevier Science Ltd2024

A Comparative Analysis of Empirical Copula and Quantile Regression Methods for Probabilistic Load Forecasting

Mario Paolone, Francesco Gerini, Pål Forr Austnes

This paper presents a detailed comparative analysis of two data-driven probabilistic forecasting methods - a density-based Empirical Copula (EC) and a non-parametric Quantile Regression (QR) - in the context of load forecasting for day-ahead market applica ...

IEEE2024

An immersive virtual reality tool for assessing left and right unilateral spatial neglect

Olaf Blanke, Andrea Serino, Roberta Ronchi

The reported rate of the occurrence of unilateral spatial neglect (USN) is highly variable likely due to the lack of validity and low sensitivity of classical tools used to assess it. Virtual reality (VR) assessments try to overcome these limitations by pr ...

Wiley2024

DiffAirfoil: An Efficient Novel Airfoil Sampler Based on Latent Space Diffusion Model for Aerodynamic Shape Optimization

Edouard Robert Albert Patrick Dufour, Colin Pelletier, Pascal Fua, Zhen Wei

Surrogate-based optimization is widely used for aerodynamic shape optimization, and its effectiveness depends on representative sampling of the design space. However, traditional sampling methods are hard-pressed to effectively sample high-dimensional desi ...

2024

Wind tunnel experiments to quantify the effect of aeolian snow transport on the surface snow microstructure

Henning Löwe, Sonja Wahl

Abstract. The evolution of the surface snow microstructure under the influence of wind during precipitation events is hardly understood but crucial for polar and alpine snowpacks. Available statistical models are solely parameterized from field data where ...

Copernicus GmbH2024

Exploiting the Signal-Leak Bias in Diffusion Models

Athanasios Fitsios, Sabine Süsstrunk, Radhakrishna Achanta, Mahmut Sami Arpa, Martin Nicolas Everaert

There is a bias in the inference pipeline of most diffusion models. This bias arises from a signal leak whose distribution deviates from the noise distribution, creating a discrepancy between training and inference processes. We demonstrate that this signa ...

2024

On the Validity of Consensus

Rachid Guerraoui, Seth Gilbert, Jovan Komatovic, Manuel José Ribeiro Vidigueira, 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

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

Robust discrete choice models with t-distributed kernel errors

Michel Bierlaire

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

2023

Comparison of questionnaire items for discomfort glare studies in daylit spaces

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

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

Bed Topography Inference from Velocity Field Using Deep Learning

Christophe Ancey, Mehrdad Kiani Oshtorjani

Measuring bathymetry has always been a major scientific and technological challenge. In this work, we used a deep learning technique for inferring bathymetry from the depth-averaged velocity field. The training of the neural network is based on 5742 labora ...

2023

Vertical and Leg Stiffness Modeling During Running: Effect of Speed and Incline

Kamiar Aminian, Grégoire Millet, Mathieu Pascal Falbriard, Frédéric Meyer

A spring mass model is often used to describe human running, allowing to understand the concept of elastic energy storage and restitution. The stiffness of the spring is a key parameter and different methods have been developed to estimate both the vertica ...

GEORG THIEME VERLAG KG2023

Stochastic particle transport by deep-water irregular breaking waves

Debbie Eeltink

Correct prediction of particle transport by surface waves is crucial in many practical applications such as search and rescue or salvage operations and pollution tracking and clean-up efforts. Recent results by Deike et al. (J. Fluid Mech., vol. 829, 2017, ...

Cambridge University Press2023

Thermal Conditions in Indoor Environments: Exploring the Reasoning behind Standard-Based Recommendations

Dolaana Khovalyg, Sarah Wael Ahmed Crosby

Professionals in the building design and operation fields typically look at standards and guidelines as a reliable source of information and guidance with regard to procedural, contractual, and legal scope and requirements that are relevant to accountabili ...

2023