Concept

Hypergeometric distribution

Related publications (15)

The HST treasury programme BUFFALO provides extended wide-field imaging of the six Hubble Frontier Fields galaxy clusters. Here we present the combined strong and weak-lensing analysis of Abell 370, a massive cluster at z = 0.375. From the reconstructed to ...

OXFORD UNIV PRESS2023

VL4Pose: Active Learning Through Out-Of-Distribution Detection For Pose Estimation

Alexandre Massoud Alahi, Megh Hiren Shukla

Advances in computing have enabled widespread access to pose estimation, creating new sources of data streams. Unlike mock set-ups for data collection, tapping into these data streams through on-device active learning allows us to directly sample from the ...

BMVA Press2022

Intrinsic area near the origin for self-similar growth-fragmentations and related random surfaces

We study the behaviour of a natural measure defined on the leaves of the genealogical tree of some branching processes, namely self-similar growth-fragmentation processes. Each particle, or cell, is attributed a positive mass that evolves in continuous tim ...

2022

Timing is Everything

Karen Adam

In this thesis, timing is everything. In the first part, we mean this literally, as we tackle systems that encode information using timing alone. In the second part, we adopt the standard, metaphoric interpretation of this saying and show the importance of ...

EPFL2022

RobustBench: a standardized adversarial robustness benchmark

Nicolas Henri Bernard Flammarion, Maksym Andriushchenko, Francesco Croce

Evaluation of adversarial robustness is often error-prone leading to overestimation of the true robustness of models. While adaptive attacks designed for a particular defense are a way out of this, there are only approximate guidelines on how to perform th ...

2020

Wasserstein Distributionally Robust Learning

Soroosh Shafieezadeh Abadeh

Many decision problems in science, engineering, and economics are affected by uncertainty, which is typically modeled by a random variable governed by an unknown probability distribution. For many practical applications, the probability distribution is onl ...

EPFL2020

Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning

Daniel Kuhn, Viet Anh Nguyen, Soroosh Shafieezadeh Abadeh, Peyman Mohajerin Esfahani

Many decision problems in science, engineering and economics are affected by uncertain parameters whose distribution is only indirectly observable through samples. The goal of data-driven decision-making is to learn a decision from finitely many training s ...

2019

Chemical inhomogeneities amongst first population stars in globular clusters Evidence for He variations

Carmela Lardo

Spreads in light element abundances among stars (also known as multiple populations) are observed in nearly all globular clusters. One way to map such chemical variations using high-precision photometry is to employ a suitable combination of stellar magnit ...

EDP SCIENCES S A2018

Dual mobility cups provide biomechanical advantages in situations at risk for dislocation: a finite element analysis

Alexandre Terrier, Adeliya Latypova, Valérie Parvex, Maïka Réane Guillemin

Purpose Constrained devices, standard implants with large heads, and dual mobility systems have become popular options to manage instability after total hip arthroplasty (THA). Clinical results with these options have shown variable success rates and signi ...

Springer Verlag2017

Geomedicine: opportunities of using spatial information to move toward more precision in public health - spatial approaches and clusters: an introduction for clinicians

Stéphane Joost, Idris Guessous

In this presentation we introduce basic knowledge about the use of located health data to detect clusters of disease prevalence. Most often, geographic maps are produced to represent health data. Medical information is transmitted through thematic chorop ...

2017

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