1. Introduction  
2. Models  
Simple Bayesian Networks  
Gaussian Bayesian Networks  
Gaussian Mixture Bayesian Networks  
Dynamic Bayesian Networks  
Hidden Markov Models  
Hidden Semi-Markov Models  
Common Bayesian Networks  
3. Algorithms  
3.1. Inference  
3.2. Learning  
4. Applications  
Channel Selection  
Classification  
Dynamics Modeling  
Augmentation by Language Modeling  
Multi-modal Integration  
5. Conclusion