Publications related to Statistics

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

Data-driven statistical optimization of a groundwater monitoring network

Andrea Rinaldo, Gianluca Botter

We propose a comparative study of three different methods aimed at optimizing existing groundwater monitoring networks. Monitoring piezometric heads in subsurface porous formations is crucial at regional scales to properly characterize the relevant subsurf ...

Elsevier2024

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

Quantitative T2 Mapping of Acute Pancreatitis

Tom Hilbert, Giulia Piazza

Background: Quantification of the T2 signal by means of T2 mapping in acute pancreatitis (AP) has the potential to quantify the parenchymal edema. Quantitative T2 mapping may overcome the limitations of previously reported scoring systems for reliable asse ...

Wiley2024

Machine learning method for the classification of the state of living organisms' oscillations

Sandor Kasas, María Inés Villalba

The World Health Organization highlights the urgent need to address the global threat posed by antibiotic-resistant bacteria. Efficient and rapid detection of bacterial response to antibiotics and their virulence state is crucial for the effective treatmen ...

Frontiers Media Sa2024

Noise-induced transitions past the onset of a steady symmetry-breaking bifurcation: The case of the sudden expansion

François Gallaire, Edouard Boujo, Yves-Marie François Ducimetière

We consider fluid flows, governed by the Navier-Stokes equations, subject to a steady symmetry-breaking bifurcation and forced by a weak noise acting on a slow timescale. By generalizing the multiple-scale weakly nonlinear expansion technique employed in t ...

2024

Network-based kinetic models: Emergence of a statistical description of the graph topology

Matteo Raviola

In this paper, we propose a novel approach that employs kinetic equations to describe the collective dynamics emerging from graph-mediated pairwise interactions in multi-agent systems. We formally show that for large graphs and specific classes of interact ...

Cambridge Univ Press2024

SUNBIRD : a simulation-based model for full-shape density-split clustering

Daniel Felipe Forero Sanchez

Combining galaxy clustering information from regions of different environmental densities can help break cosmological parameter degeneracies and access non-Gaussian information from the density field that is not readily captured by the standard two-point c ...

2024

Beyond the average consumer: Mapping the potential of demand-side management among patterns of appliance usage

Claudia Rebeca Binder Signer, Matteo Barsanti, Selin Yilmaz

To support the decarbonisation of the power sector and offset the volatility of a system with high levels of renewables, there is growing interest in residential Demand-Side Management (DSM) solutions. Traditional DSM strategies require consumers to active ...

2024

Spatial Modeling for Building Design Evaluation: from Visual Landscape Quality Assessment to Devaluation Risk Estimation

Adam Robert Swietek

Zoning reform is a crucial tool for cities to adapt to contemporary challenges. However, its implementation remains challenging. Property owners, with a vested interest in the value of their neighborhoods, are sensitive to local developments and the potent ...

EPFL2024

We Need Subject Matter Expertise to Choose and Identify Causal Estimands: Comment on "Estimands for Recurrent Event Endpoints in the Presence of a Terminal Event"

Matias Janvin, Mats Julius Stensrud

We summarize what we consider to be the two main limitations of the "Estimands for Recurrent Event Endpoints in the Presence of a Terminal Event" (Schmidli et al. 2022). First, the authors did not give detailed guidance on how to choose an appropriate esti ...

TAYLOR & FRANCIS INC2023

DESI mock challenge Halo and galaxy catalogues with the bias assignment method

Cheng Zhao, Ginevra Favole, Yu Yu

Context. We present a novel approach to the construction of mock galaxy catalogues for large-scale structure analysis based on the distribution of dark matter halos obtained with effective bias models at the field level. Aims. We aim to produce mock galaxy ...

EDP SCIENCES S A2023

Euclid preparation: XXVIII. Forecasts for ten different higher-order weak lensing statistics

Frédéric Courbin, Gianluca Castignani, Austin Chandler Peel, Jean-Luc Starck, Maurizio Martinelli, Yi Wang, Richard Massey, Fabio Finelli, Marcello Farina

Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale ...

EDP SCIENCES S A2023

Networks with correlated edge processes

Sofia Charlotta Olhede, Mária Süveges

This article proposes methods to model non-stationary temporal graph processes motivated by a hospital interaction data set. This corresponds to modelling the observation of edge variables indicating interactions between pairs of nodes exhibiting dependenc ...

OXFORD UNIV PRESS2023

Diverse parameters of ambulatory knee moments differ with medial knee osteoarthritis severity and are combinable into a severity index

Julien Favre, Brigitte Jolles-Haeberli

Objective: To characterize ambulatory knee moments with respect to medial knee osteoarthritis (OA) severity comprehensively and to assess the possibility of developing a severity index combining knee moment parameters. ...

FRONTIERS MEDIA SA2023

Static and Dynamic Stochastic Analysis of a Temperature-Sensitive VO2 Spiking Neuron

Mihai Adrian Ionescu, Teodor Rosca

In this work, we investigate the intrinsic cycle-to-cycle variations in a spiking temperature-sensitive neuron, based on the resistive switching of a Vanadium dioxide (VO2) two-terminal device. We study how this phenomenon impacts the spike rate jitter, an ...

IEEE2023

Machine Learning Security in Industry: A Quantitative Survey

Kathrin Grosse

Despite the large body of academic work on machine learning security, little is known about the occurrence of attacks on machine learning systems in the wild. In this paper, we report on a quantitative study with 139 industrial practitioners. We analyze at ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

An Unbiased Method of Measuring the Ratio of Two Data Sets

Jean-Paul Richard Kneib, Huanyuan Shan

In certain cases of astronomical data analysis, the meaningful physical quantity to extract is the ratio R between two data sets. Examples include the lensing ratio, the interloper rate in spectroscopic redshift samples, and the decay rate of gravitational ...

IOP Publishing Ltd2023

GEAR-RT: Towards Exa-Scale Moment Based Radiative Transfer For Cosmological Simulations Using Task-Based Parallelism And Dynamic Sub-Cycling with SWIFT

Mladen Ivkovic

Numerical simulations have become an indispensable tool in astrophysics and cosmology. The constant need for higher accuracy, higher resolutions, and models of ever-increasing sophistication and complexity drives the development of modern tools which targe ...

EPFL2023

GTC Follow-up Observations of Very Metal-poor Star Candidates from DESI

Pascale Jablonka, Arjun Dey

The observations from the Dark Energy Spectroscopic Instrument (DESI) will significantly increase the numbers of known extremely metal-poor stars by a factor of similar to 10, improving the sample statistics to study the early chemical evolution of the Mil ...

Iop Publishing Ltd2023