Publications associées à Combining Statistical Evidence

Understanding and Enhancing Digital Wellbeing Dimensions: Empirical Studies on Smartphone Usage Patterns and Recommendations of Micro-Informative Content

Digital technology has become an integral part of our lives, offering various benefits from communication and entertainment to education and productivity. However, its pervasive use has also raised concerns about its potential negative impact on users' wel ...

EPFL2024

Technosignatures Longevity and Lindy's Law

Claudio Grimaldi

The probability of detecting technosignatures (i.e., evidence of technological activity beyond Earth) increases with their longevity, or the time interval over which they manifest. Therefore, the assumed distribution of longevities has some bearing on the ...

Iop Publishing Ltd2024

Neutrino Signal from a Population of Seyfert Galaxies

Andrii Neronov

IceCube Collaboration has previously reported evidence for a neutrino signal from a Seyfert galaxy NGC 1068. This may suggest that all Seyfert galaxies emit neutrinos. To test this hypothesis, we identify the best candidate neutrino sources among nearby Se ...

Amer Physical Soc2024

A state-of-the-art, systematic review of indoor environmental quality studies in work-from-home settings

Giorgia Chinazzo

The COVID-19 pandemic has led to a significant increase in working from home worldwide, making the workfrom-home (WFH) setting a crucial context for studying the influence of indoor environmental quality (IEQ) on workers' well-being and productivity. A nar ...

Pergamon-Elsevier Science Ltd2024

A comprehensive review on geomembrane systems application in hydropower

Giovanni De Cesare, Samuel Luke Vorlet

Geomembrane systems have been used at hydropower plants as rehabilitation and mitigation technology for several decades and are now used worldwide. In the context of planning an energy transition that promotes the sustainable use of water resources for ene ...

2024

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

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

Holography and localization of information in quantum gravity

Kyriakos Papadodimas, Alexandre Mathieu Frédéric Belin

Within the AdS/CFT correspondence, we identify a class of CFT operators which represent diff-invariant and approximately local observables in the gravitational dual. Provided that the bulk state breaks all asymptotic symmetries, we show that these operator ...

Springer Nature2024

Transdiagnostic markers across the psychosis continuum: a systematic review and meta-analysis of resting state fMRI studies

Dimitri Nestor Alice Van De Ville, Farnaz Delavari

Psychotic symptoms are among the most debilitating and challenging presentations of severe psychiatric diseases, such as schizophrenia, schizoaffective, and bipolar disorder. A pathophysiological understanding of intrinsic brain activity underlying psychos ...

Frontiers Media Sa2024

Artificial intelligence of things for synergizing smarter eco-city brain, metabolism, and platform: Pioneering data-driven environmental governance

Jeffrey Huang, Simon Elias Bibri

Emerging smarter eco-cities, inherently intertwined with environmental governance, function as experimental sites for testing novel technological solutions and implementing environmental reforms aimed at addressing complex challenges. However, despite sign ...

Elsevier2024

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

Dolaana Khovalyg

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

When do Minimax-fair Learning and Empirical Risk Minimization Coincide?

Volkan Cevher

Minimax-fair machine learning minimizes the error for the worst-off group. However, empirical evidence suggests that when sophisticated models are trained with standard empirical risk minimization (ERM), they often have the same performance on the worst-of ...

2023

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

Learning Transformations To Reduce the Geometric Shift in Object Detection

Mathieu Salzmann, Martin Pierre Engilberge, Vidit Vidit

The performance of modern object detectors drops when the test distribution differs from the training one. Most of the methods that address this focus on object appearance changes caused by, e.g., different illumination conditions, or gaps between syntheti ...

Ieee Computer Soc2023

Single fraction and hypofractionated radiosurgery for perioptic meningiomas-tumor control and visual outcomes: a systematic review and meta-analysis

Constantin Tuleasca

Perioptic meningiomas, defined as those that are less than 3 mm from the optic apparatus, are challenging to treat with stereotactic radiosurgery (SRS). Tumor control must be weighed against the risk of radiation-induced optic neuropathy (RION), as both tu ...

Springer2023

Predicting party switching through machine learning and open data

Silvestro Micera, Emanuele Rossi

Parliament dynamics might seem erratic at times. Predicting future voting patterns could support policy design based on the simulation of voting scenarios. The availability of open data on legislative activities and machine learning tools might enable such ...

CELL PRESS2023

Search for dark photon decays to μ+μ- at NA62

Radoslav Marchevski, Alina Kleimenova

The NA62 experiment at CERN, designed to study the ultra-rare decay K+ -> pi(+) nu(nu) over bar, has also collected data in beam-dump mode. In this configuration, dark photons may be produced by protons dumped on an absorber and reach a decay volume beginn ...

Springer Nature2023

Ricca's factors as mobile proteinaceous effectors of electrical signaling

Jian Wang, Satyam Tiwari

Leaf-feeding insects trigger high-amplitude, defense-inducing electrical signals called slow wave potentials (SWPs). These signals are thought to be triggered by the long-distance transport of low molecular mass elicitors termed Ricca's factors. We sought ...

CELL PRESS2023

Atomistic modeling of C-S-H: bulk and surface

Ziga Casar

By replacing part of Portland cement with so-called supplementary cementitious materials (SCMs) it is possible to reduce the CO2 footprint of the cement industry. These SCMs are commonly limestone, calcined clay, slag and fly ash. While doing so the early ...

EPFL2023

Single-fraction radiosurgery outcomes for large vestibular schwannomas in the upfront or post-surgical setting: a systematic review and International Stereotactic Radiosurgery Society (ISRS) Practice Guidelines

Constantin Tuleasca

PurposeTo perform a systematic review of literature specific to single-fraction stereotactic radiosurgery (SRS) for large vestibular schwannomas (VS), maximum diameter >= 2.5 cm and/or classified as Koos Grade IV, and to present consensus recommendations o ...

Springer2023