Space Oddity? A Statistical Formulation of Conjunction Assessment

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Safety climate in university laboratories. Part I: model development and practical application

Thierry Meyer, Anastasia Jung

Safety climate assessment has become a regular practice for most organisations. However, it is often limited to questionnaires, providing only qualitative information. The indicator-based approach takes precedence over decision-making, and practical risk a ...

2023

Wind, Hail, and Climate Extremes: Modelling and Attribution Studies for Environmental Data

Ophélia Mireille Anna Miralles

This thesis presents work at the junction of statistics and climate science. We first provide methodology for use by climate scientists when performing fast event attribution using extreme value theory, and then describe two interdisciplinary projects in c ...

EPFL2023

Distribution Inference Risks: Identifying and Mitigating Sources of Leakage

Robert West, Maxime Jean Julien Peyrard, Valentin Hartmann, Léo Nicolas René Meynent

A large body of work shows that machine learning (ML) models can leak sensitive or confidential information about their training data. Recently, leakage due to distribution inference (or property inference) attacks is gaining attention. In this attack, the ...

IEEE COMPUTER SOC2023

Combining European and US risk prediction models with polygenic risk scores to refine cardiovascular prevention: the CoLaus|PsyCoLaus Study

Jacques Fellay, Christian Axel Wandall Thorball, Stéphane Fournier, Roxane De La Harpe

Lay Summary The aim of this study is to determine whether using polygenic risk scores improves the prediction of atherosclerotic cardiovascular disease risk when combined with clinical scores currently recommended by European and US guidelines on cardiovas ...

OXFORD UNIV PRESS2023

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Elisabetta Cornacchia

This thesis focuses on two selected learning problems: 1) statistical inference on graphs models, and, 2) gradient descent on neural networks, with the common objective of defining and analysing the measures that characterize the fundamental limits. In th ...

EPFL2023

Partial Information Sharing Over Social Learning Networks

Ali H. Sayed, Virginia Bordignon

This work addresses the problem of sharing partial information within social learning strategies. In social learning, agents solve a distributed multiple hypothesis testing problem by performing two operations at each instant: first, agents incorporate inf ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

The imprint of galaxy mergers on satellite planes in a cosmological context

Oliver Müller

Flattened and kinematically correlated planes of dwarf satellite galaxies have been observed in the Local Volume. The slinging out of satellites during host galaxy mergers has been suggested as a formation mechanism for these peculiar structures. We statis ...

2023

Closed form approximation methods for portfolio valuation and risk management

Lotfi Boudabsa

In this thesis we present three closed form approximation methods for portfolio valuation and risk management. The first chapter is titled ``Kernel methods for portfolio valuation and risk management'', and is a joint work with Damir Filipovi'c (SFI and ...

EPFL2023

The development, validation and use of an interprofessional project management questionnaire in engineering education

Roland John Tormey, Marc Laperrouza

Professional skills of project planning, risk analysis, ethical design, communication, and working in interprofessional teams are now recognised as core engineering skills. Frequently, they are addressed in engineering education through team projects. Howe ...

2023

Filtered data and eigenfunction estimators for statistical inference of multiscale and interacting diffusion processes

Andrea Zanoni

We study the problem of learning unknown parameters of stochastic dynamical models from data. Often, these models are high dimensional and contain several scales and complex structures. One is then interested in obtaining a reduced, coarse-grained descript ...

EPFL2022

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Combining European and US risk prediction models with polygenic risk scores to refine cardiovascular prevention: the CoLaus|PsyCoLaus Study

Jacques Fellay, Christian Axel Wandall Thorball, Stéphane Fournier, Roxane De La Harpe

OXFORD UNIV PRESS2023