Lecturer: Vaclav Smidl

Lesson 1: Review of probability and trivial models

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Lesson 2: Prior and Approximate posteriors

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Lesson 3: Monte Carlo Methods

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Lesson 4: Linear Regression

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• ETEX experiment

Lesson 5: Blind Source Separation

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• Toy problem

Lesson 6: Mixture Models

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• Patlak plot analysis

Lesson 7: Mixture of Regressors

• Pdf presentation
• Patlak plot EM
• Dirichlet sampler

Lesson 8: Bayesian Filtering

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Lesson 9: Bayesian Filtering

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• Data for force estimation
• Script kalman.m
• Demo of sine wave example

Lesson 10: Bayesian Non-linear regression

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• Data for toy network