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A Bayesian Approach to Detect Pedestrian Destination-Sequences from WiFi Signatures

Related publications (27)

Bayesian regression explains how human participants handle parameter uncertainty

Jean-Pascal Théodor Pfister, Michael Herzog, Maya Anna Jastrzebowska, Mattew Pachai

Author summary How do humans make prediction when the critical factor that influences the quality of the prediction is hidden? Here, we address this question by conducting a simple psychophysical experiment in which participants had to extrapolate a parabo ...

2020

Design and analysis of control strategies for pedestrian flows

Michel Bierlaire, Nicholas Alan Molyneaux, Riccardo Scarinci

Exploiting the full potential of pedestrian infrastructure is becoming critical in many environments which cannot be easily expanded to cope with the increasing pedestrian demand. This is particularly true for train stations as in many dense cities space i ...

SPRINGER2021

A Bayesian numerical homogenization method for elliptic multiscale inverse problems

Assyr Abdulle, Andrea Di Blasio

A new strategy based on numerical homogenization and Bayesian techniques for solving multiscale inverse problems is introduced. We consider a class of elliptic problems which vary at a microscopic scale, and we aim at recovering the highly oscillatory tens ...

2020

Bayesian modeling of brain function and behavior

Maya Anna Jastrzebowska

The application of Bayesian modeling techniques is increasingly common in neuroscience due to the coherent and principled way in which the paradigm deals with uncertainty. The Bayesian framework is particularly valuable in the context of complex, ill-posed ...

EPFL2020

On Vacuous and Non-Vacuous Generalization Bounds for Deep Neural Networks

Konstantinos Pitas

Deep neural networks have been empirically successful in a variety of tasks, however their theoretical understanding is still poor. In particular, modern deep neural networks have many more parameters than training data. Thus, in principle they should over ...

EPFL2020

TDCOSMO. IV. Hierarchical time-delay cosmography - joint inference of the Hubble constant and galaxy density profiles

Frédéric Courbin, Martin Raoul Robert Millon, Aymeric Alexandre Galan, Adriano Agnello

The H0LiCOWcollaboration inferred via strong gravitational lensing time delays a Hubble constant value of H0 = 73 :3+1:7 1:8 km s 1 Mpc 1, describing deflector mass density profiles by either a power-law or stars (constant mass-to-light ratio) plus standar ...

EDP SCIENCES S A2020

The Learnability of the Grammar of Jazz: Bayesian Inference of Hierarchical Structures in Harmony

Daniel Harasim

Musical grammar describes a set of principles that are used to understand and interpret the structure of a piece according to a musical style. The main topic of this study is grammar induction for harmony --- the process of learning structural principles f ...

EPFL2020