Publications related to Statistical model specification

Spectral Estimators for High-Dimensional Matrix Inference

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

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

Fragment ion-functional group relationships in organic aerosols using aerosol mass spectrometry and mid-infrared spectroscopy

Satoshi Takahama, Amir Yazdani, Imad El Haddad, Nikunj Dudani

Aerosol mass spectrometry (AMS) and mid-infrared spectroscopy (MIR) are two analytical methods for characterizing the chemical composition of OM. While AMS provides high-temporal-resolution bulk measurements, the extensive fragmentation during the electron ...

2022

Financial Risk Management with Machine Learning

Marc-Aurèle Antoine Divernois

This thesis consists of three applications of machine learning techniques to risk management. The first chapter proposes a deep learning approach to estimate physical forward default intensities of companies. Default probabilities are computed using artifi ...

EPFL2022

Mutual information for low-rank even-order symmetric tensor estimation

Nicolas Macris, Jean François Emmanuel Barbier, Clément Dominique Luneau

We consider a statistical model for finite-rank symmetric tensor factorization and prove a single-letter variational expression for its asymptotic mutual information when the tensor is of even order. The proof applies the adaptive interpolation method orig ...

OXFORD UNIV PRESS2021

Discrete-Choice Mining of Social Processes

Victor Kristof

Poor decisions and selfish behaviors give rise to seemingly intractable global problems, such as the lack of transparency in democratic processes, the spread of conspiracy theories, and the rise in greenhouse gas emissions. However, people are more predict ...

EPFL2021

Population pharmacokinetic model selection assisted by machine learning

Jan Sickmann Hesthaven, Nadia Terranova

A fit-for-purpose structural and statistical model is the first major requirement in population pharmacometric model development. In this manuscript we discuss how this complex and computationally intensive task could benefit from supervised machine learni ...

SPRINGER/PLENUM PUBLISHERS2022

Disparity Between Batches as a Signal for Early Stopping

Patrick Thiran, Mahsa Forouzesh

We propose a metric for evaluating the generalization ability of deep neural networks trained with mini-batch gradient descent. Our metric, called gradient disparity, is the l2 norm distance between the gradient vectors of two mini-batches drawn from the t ...

Springer2021

Simultaneous autoregressive models for spatial extremes

Emeric Rolland Georges Thibaud

Motivated by the widespread use of large gridded data sets in the atmospheric sciences, we propose a new model for extremes of areal data that is inspired by the simultaneous autoregressive (SAR) model in classical spatial statistics. Our extreme SAR model ...

WILEY2020

Improve the Model Stability of Dam's Displacement Prediction Using a Numerical-Statistical Combined Model

Zhenzhu Meng, Yating Hu, Chenfei Shao

In most studies of dam's displacement prediction based on monitoring data, emphasis was given on improving the prediction accuracy, while the model stability was merely considered. This study proposed a numerical-statistical combined model which aims to im ...

2020

Parameter Estimation of Three-Phase Untransposed Short Transmission Lines from Synchrophasor Measurements

Jean-Yves Le Boudec, Mario Paolone, Arpan Mukhopadhyay

We present a new approach for estimating the parameters of three-phase untransposed electrically short transmission lines using voltage/current synchrophasor measurements obtained from phasor measurement units. The parameters to be estimated are the entrie ...

2020

Multiple dehydrogenation reactions of negative ions in low pressure silane plasma chemistry

Christoph Hollenstein, Alan Howling, Antoine Descoeudres

Micro-particle formation in low pressure silane (SiH4) plasmas has been of technical interest and concern for at least 40 years. Negative ion plasma chemistry is a candidate for the initial nucleation, which has been extensively studied both experimentally ...

2020

Enhancing discrete choice models with representation learning

Alexandre Massoud Alahi, Virginie Janine Camille Lurkin

In discrete choice modeling (DCM), model misspecifications may lead to limited predictability and biased parameter estimates. In this paper, we propose a new approach for estimating choice models in which we divide the systematic part of the utility specif ...

2020

Radiative cooling of carbon cluster anions C-2n+1(-) (n=3-5)

Eduardo Carrascosa Casado

Radiative cooling of carbon cluster anions C(2n+1)(-)C2n+1- (n = 3-5) is investigated using the cryogenic electrostatic ion storage ring DESIREE. Two different strategies are applied to infer infrared emission on slow (milliseconds to seconds) and ultraslo ...

SPRINGER2020

A User Study of Perceived Carbon Footprint

Patrick Thiran, Matthias Grossglauser, Victor Kristof, Robin Adrien Zbinden, Lucas Maystre, Valentin Quelquejay-Leclère

We propose a statistical model to understand people's perception of their carbon footprint. Driven by the observation that few people think of CO2 impact in absolute terms, we design a system to probe people's perception from simple pairwise comparisons of ...

2019

Mutual Information for Low-Rank Even-Order Symmetric Tensor Factorization

Nicolas Macris, Jean François Emmanuel Barbier, Clément Dominique Luneau

We consider a statistical model for finite-rank symmetric tensor factorization and prove a single-letter variational expression for its mutual information when the tensor is of even order. The proof uses the adaptive interpolation method, for which rank-on ...

IEEE2019

Statistical Model of Measurement Noise in Real-World PMU-based Acquisitions

Mario Paolone, Asja Derviskadic, Guglielmo Frigo, Alexandre Bach

In this paper, we present a processing technique to determine the statistical distribution of additive measurement noise in real-world acquisitions, with specific reference to Phasor Measurement Unit (PMU) applications in Active Distribution Networks (ADNs ...

IEEE2019

Contributions to Likelihood-Based Modelling of Extreme Values

Léo Raymond-Belzile

xtreme value analysis is concerned with the modelling of extreme events such as floods and heatwaves, which can have large impacts. Statistical modelling can be useful to better assess risks even if, due to scarcity of measurements, there is inherently ver ...

EPFL2019

A Data-Driven Approach Based on Multivariate Copulas for Quantitative Risk Assessment of Concrete Dam

Zhenzhu Meng, Yating Hu, Chenfei Shao

Risk assessment of dam's running status is an important part of dam management. A data-driven method based on monitored displacement data has been applied in risk assessment, owing to its easy operation and real-time analysis. However, previous data-driven ...

2019

Automatic L2 Regularization for Multiple Generalized Additive Models

Yousra El Bachir

Multiple generalized additive models are a class of statistical regression models wherein parameters of probability distributions incorporate information through additive smooth functions of predictors. The functions are represented by basis function expan ...

EPFL2019