Bayesian programming Lab

Juan-Manuel Ahuactzin Larios

Probayes SAS. 345, rue Lavoisier, Inovallée 38330 Saint Ismier Cedex, France

This is the practical sessions of Bayesian Programming where we teach a second level of expertise: how to develop and implement a computer program effectively that includes some Bayesian computation. Programs will be developed in ProBT© a C++ multi-platform library used to automate probabilistic calculus. The ProBT® library has two main components: (i) a friendly Application Program Interface (API) for building Bayesian models and (ii) a high-performance Bayesian Inference Engine (BIE) allowing execution of the probability calculus in exact or approximate modes.

CONTENT

• Variables
• Distributions
• Bayesian networks
• Types of reasoning
• Mixture models
• Naïve Bayes
  • Parameter estimation
  • Classification
  • Sensor fusion
• HMM
• Bayesian filter
• Particles filter
• Learning