Bayes AI Slides
Author
Vadim Sokolov
George Mason University
Spring 2025
Published
March 3, 2025
Unit 1: Introduction: AI Today and in the Past. Probability and Bayes Rule
Unit 2: Utility and Decision Theory
Unit 3: Bayesian Inference with Conjugate Pairs
Unit 4: Markov Chain Monte Carlo
Unit 5: Bayesian Regression: Linear and Bayesian Trees
Unit 6: Stochastic Processes
Unit 7: Bayesian Hypothesis Tests
Unit 8: Quantile Neural Networks for Reinforcement Learning and Uncertainty Quantification
Unit 9: Bayesian Double Descent and Model Selection: Modern Approach to Bias-Variance Tradeoff
Unit 10: Bayesian Neural Networks and Deep Learning
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