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Functional estimation of anisotropic covariance and autocovariance operators on the sphere

Victor Panaretos, Matthieu Martin Jean-André Simeoni, Julien René Pierre Fageot, Alessia Caponera

We propose nonparametric estimators for the second-order central moments of possibly anisotropic spherical random fields, within a functional data analysis context. We consider a measurement framework where each random field among an identically distribute ...

2022

Discrete Optimal Transport with Independent Marginals is #P-Hard

Daniel Kuhn, Soroosh Shafieezadeh Abadeh, Bahar Taskesen

We study the computational complexity of the optimal transport problem that evaluates the Wasser- stein distance between the distributions of two K-dimensional discrete random vectors. The best known algorithms for this problem run in polynomial time in th ...

2023

Acceleration of gossip algorithms through the Euler-Poisson-Darboux Equation

Raphaël Jean Berthier

Gossip algorithms and their accelerated versions have been studied exclusively in discrete time on graphs. In this work, we take a different approach and consider the scaling limit of gossip algorithms in both large graphs and large number of iterations. T ...

OXFORD UNIV PRESS2022

Strategic Insights into Engineering Parameters Affecting Cell Type-Specific Uptake of DNA-Based Nanomaterials

Maartje Martina Cornelia Bastings, Alice Comberlato, Hugo José Rodriguez Franco, Marianna Mainardi Koga

DNA-based nanomaterials are gaining popularity as uniform and programmable bioengineering tools as a result of recent solutions to their weak stability under biological conditions. The DNA nanotechnology platform uniquely allows decoupling of engineering p ...

American Chemical Society2022

From Trees to Barcodes and Back Again: A Combinatorial, Probabilistic and Geometric Study of a Topological Inverse Problem

Adélie Eliane Garin

In this thesis, we investigate the inverse problem of trees and barcodes from a combinatorial, geometric, probabilistic and statistical point of view. Computing the persistent homology of a merge tree yields a barcode B. Reconstructing a tree from B invol ...

EPFL2022

Using wavelets to capture deviations from smoothness in galaxy-scale strong lenses

Frédéric Courbin, Aymeric Alexandre Galan, Georgios Vernardos, Austin Chandler Peel

Modeling the mass distribution of galaxy-scale strong gravitational lenses is a task of increasing difficulty. The high-resolution and depth of imaging data now available render simple analytical forms ineffective at capturing lens structures spanning a la ...

EDP SCIENCES S A2022

An Efficient Signal-to-noise Approximation for Eccentric Inspiraling Binaries

Alexandra Shelest

Eccentricity has emerged as a potentially useful tool for helping to identify the origin of black hole mergers. However, eccentric templates can be computationally very expensive owing to the large number of harmonics, making statistical analyses to distin ...

IOP Publishing Ltd2022

Perturbation theory models for LSST-era galaxy clustering: Tests with subpercent mock catalog measurements in Fourier and configuration space

Jonathan Andrew Blazek

We analyze the clustering of galaxies using the z = 1.006 snapshot of the CosmoDC2 simulation, a high-fidelity synthetic galaxy catalog designed to validate analysis methods for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). We prese ...

American Physical Society2022

Multi-Level Monte Carlo Methods for Uncertainty Quantification and Risk-Averse Optimisation

Sundar Subramaniam Ganesh

This work aims to study the effects of wind uncertainties in civil engineering structural design. Optimising the design of a structure for safety or operability without factoring in these uncertainties can result in a design that is not robust to these per ...

EPFL2022

Predictive models for response to non-invasive brain stimulation in stroke: A critical review of opportunities and pitfalls

Philip Egger, Friedhelm Christoph Hummel, Maximilian Jonas Wessel

Background: Noninvasive brain stimulation has been successfully applied to improve stroke impairments in different behavioral domains. Yet, clinical translation is limited by heterogenous comes within and across studies. It has been proposed to develop and ...

ELSEVIER SCIENCE INC2021

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Discrete Optimal Transport with Independent Marginals is #P-Hard

Daniel Kuhn, Soroosh Shafieezadeh Abadeh, Bahar Taskesen

2023

From Trees to Barcodes and Back Again: A Combinatorial, Probabilistic and Geometric Study of a Topological Inverse Problem

Adélie Eliane Garin

EPFL2022

An Efficient Signal-to-noise Approximation for Eccentric Inspiraling Binaries

Alexandra Shelest

IOP Publishing Ltd2022

Perturbation theory models for LSST-era galaxy clustering: Tests with subpercent mock catalog measurements in Fourier and configuration space

Jonathan Andrew Blazek

American Physical Society2022

Predictive models for response to non-invasive brain stimulation in stroke: A critical review of opportunities and pitfalls

Philip Egger, Friedhelm Christoph Hummel, Maximilian Jonas Wessel

ELSEVIER SCIENCE INC2021