Institute of Information Theory and Automation

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Hierarchical Bayesian Models

Lecturer: Vaclav Smidl

Lesson 1: Review of probability and trivial models

Lesson 2: Prior and Approximate posteriors

Lesson 3: Linear regression

Lesson 4: Mixture models

Lesson 5: Mixture model challenge (Patlak)

Lesson 6: Monte Carlo

Lesson 7: Bayesian Filtering

Lesson 8: Bayesian Filtering - examples

 

Lesson 9: Correlated prior and time series 

Lesson 10: Bayesian non-linear regression

Lesson 11: ELBO and Variational Autoencoder

2020-05-19 22:29