Concept

Bayesian probability

Related publications (388)

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Cross-lingual Linking of Multi-word Entities and their corresponding Acronyms

Maud Ehrmann

This paper reports on an approach and experiments to automatically build a cross-lingual multi-word entity resource. Starting from a collection of millions of acronym/expansion pairs for 22 languages where expansion variants were grouped into monolingual c ...

European Language Resources Association (ELRA)2016

Bayesian Inference For The Brown-Resnick Process, With An Application To Extreme Low Temperatures

Anthony Christopher Davison, Emeric Rolland Georges Thibaud

The Brown-Resnick max-stable process has proven to be well suited for modeling extremes of complex environmental processes, but in many applications its likelihood function is intractable and inference must be based on a composite likelihood, thereby preve ...

Inst Mathematical Statistics2016

The Bullet cluster at its best: weighing stars, gas, and dark matter

Jean-Paul Richard Kneib, Danuta Janina Paraficz, Johan Richard

Aims. We present a new strong lensing mass reconstruction of the Bullet cluster (1E 0657-56) at z = 0 : 296, based on WFC3 and ACS HST imaging and VLT/FORS2 spectroscopy. The strong lensing constraints underwent substantial revision compared to previously ...

Edp Sciences S A2016

An overview of quantitative approaches in Gestalt perception

Michael Herzog

Gestalt psychology is often criticized as lacking quantitative measurements and precise mathematical models. While this is true of the early Gestalt school, today there are many quantitative approaches in Gestalt perception and the special issue of Vision ...

Elsevier2016

Balancing New Against Old Information: The Role of Surprise

Wulfram Gerstner, Kerstin Preuschoff, Mohammadjavad Faraji

Surprise is a widely used concept describing a range of phenomena from unexpected events to behavioral responses. We propose a measure of surprise, to arrive at a new framework for surprise-driven learning. There are two components to this framework: (i) a ...

Public Library of Science2016

Combine and Conquer

Vincent Etter

In this thesis, we explore the application of data mining and machine learning techniques to several practical problems. These problems have roots in various fields such as social science, economics, and political science. We show that computer science tec ...

EPFL2015

A Bayesian Approach for Pervasive Estimation of Breaststroke Velocity Using a Wearable IMU

Kamiar Aminian, Grégoire Millet, Farzin Dadashi

An ubiquitous assessment of swimming velocity (main metric of the performance) is essential for the coach to provide a tailored feedback to the trainee. We present a probabilistic framework for the data-driven estimation of the swimming velocity at every c ...

Elsevier Science Bv2015

The impact of customer behavior models on revenue management systems

Shadi Sharif Azadeh

Revenue management (RM) can be considered an application of operations research in the transportation industry. For these service companies, it is a difficult task to adjust supply and demand. In order to maximize revenue, RM systems display demand behavio ...

2015

Objective Bayesian Model Selection

Thomas Lugrin

Frequentist and Bayesian approaches to statistics have long been seen as incompatible, but recent work has been done to try and unify them (Bayarri and Berger, 2004; Efron, 2005). Empirical Bayes, approximate Bayesian analysis, and the matching prior appro ...

2015

Infection Spread In Random Geometric Graphs

Ghurumuruhan Ganesan

In this paper we study the speed of infection spread and the survival of the contact process in the random geometric graph G = G (n, r(n), f) of n nodes independently distributed in S = -1/2, 1/2 according to a certain density f(.). In the first part ...

Applied Probability Trust2015