Skip to Main content Skip to Navigation
Conference papers

A Survey of Probabilistic Models Using the Bayesian Programming Methodology as a Unifying Framework

Julien Diard 1 Pierre Bessiere 1 Emmanuel Mazer 1
1 E-MOTION - Geometry and Probability for Motion and Action
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes
Abstract : This paper presents a survey of the most common probabilistic models for artefact conception. We use a generic formalism called Bayesian Programming, which we introduce briefly, for reviewing the main probabilistic models found in the literature. Indeed, we show that Bayesian Networks, Markov Localization, Kalman filters, etc., can all be captured under this single formalism. We believe it offers the novice reader a good introduction to these models, while still providing the experience reader an enriching global view of the field.
Complete list of metadata

https://hal.archives-ouvertes.fr/hal-00019254
Contributor : Pierre Bessiere <>
Submitted on : Friday, March 10, 2006 - 12:00:15 PM
Last modification on : Monday, December 28, 2020 - 3:44:02 PM
Long-term archiving on: : Saturday, April 3, 2010 - 10:29:47 PM

Identifiers

  • HAL Id : hal-00019254, version 1

Collections

INRIA | IMAG | CNRS | UGA

Citation

Julien Diard, Pierre Bessiere, Emmanuel Mazer. A Survey of Probabilistic Models Using the Bayesian Programming Methodology as a Unifying Framework. --, 2003, France. ⟨hal-00019254⟩

Share

Metrics

Record views

679

Files downloads

1312