Week 4

Lecture

• Lecture #6: Monte Carlo Integration
  • Lecture Video
  • Lecture Notes
  • Lecture Summary
• Lecture #7: Markov Chain Monte Carlo
  • Lecture Video
  • Lecture Notes
  • Lecture Summary

Activities

• In-Class Exercise #6: Monte Carlo Integration
• In-Class Exercise #6: Solutions
• In-Class Exercise #7: Introduction to MCMC
• In-Class Exercise #7: Solutions
• Homework #3
• Homework #3 Solutions

Reading

Applications and Broader Impact

1. Small Data Can Play a Big Role in AI
2. Incorporating Bayesian Ideas into Health-Care Evaluation
3. A Bayesian Modelling Approach with Balancing Informative Prior for Analysing Imbalanced Data
4. On Using Bayesian Methods to Address Small Sample Problems

Monte Carlo Integration

1. (Introductory) Monte Carlo Integration
2. (Advanced) Safe and Effective Importance Sampling

Markov Chain Monte Carlo

1. (Introductory) Gibbs Sampling for the Uninitiated
2. (Introductory) Finite State Markov Chains: A Linear Algebra Treatment
3. (In Depth) Probabilistic Inference Using Markov Chain Monte Carlo Methods