Learning and Reasoning with Bayesian Networks

Learning and Reasoning with Bayesian Networks

UCLA Automated Reasoning Group via YouTube Direct link

1a. Course Overview with a Historical Perspective on AI

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1a. Course Overview with a Historical Perspective on AI

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Classroom Contents

Learning and Reasoning with Bayesian Networks

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  1. 1 1a. Course Overview with a Historical Perspective on AI
  2. 2 1b. Propositional Logic (Chapter 2)
  3. 3 2a. Probability Calculus: Beliefs and Hard Evidence (Chapter 3)
  4. 4 2b. Probability Calculus: Soft Evidence (Chapter 3)
  5. 5 3a. Bayesian Networks: Syntax and Semantics (Chapter 4)
  6. 6 3b. Bayesian Networks: Independence and d-Separation (Chapter 4)
  7. 7 4a. Probabilistic Queries and their Complexity (Chapter 5)
  8. 8 4b. Building Bayesian Networks I (Chapter 5)
  9. 9 5a. Building Bayesian Networks II (Chapter 5)
  10. 10 5b. Building Bayesian Networks III (Chapter 5)
  11. 11 6a. Inference by Variable Elimination I (Chapter 6)
  12. 12 6b. Inference by Variable Elimination II (Chapter 6)
  13. 13 7a. The Jointree Algorithm (Chapter 7)
  14. 14 7b. Inference by Conditioning (Chapter 8)
  15. 15 8a. Arithmetic Circuits I (Chapter 12)
  16. 16 8b. Arithmetic Circuits II (Chapter 12)
  17. 17 9a. Arithmetic Circuits & SPNs
  18. 18 9b. Arithmetic Circuits & PSDDs
  19. 19 10a. Loopy Belief Propagation (Chapter 14)
  20. 20 10b. Relax, Compensate, then Recover (Chapter 14)
  21. 21 11a. Learning Parameters: Complete Data (Chapter 17)
  22. 22 11b. Learning Parameters: Incomplete Data (Chapter 17)
  23. 23 12a. Learning Network Structure I (Chapter 17)
  24. 24 12b. Learning Network Structure II (Chapter 17)
  25. 25 13a. Bayesian Learning: Discrete Parameter Sets I (Chapter 18)
  26. 26 13b. Bayesian Learning: Discrete Parameter Sets II (Chapter 18)
  27. 27 14. Bayesian Learning: Dirichlet Priors (Chapter 18)
  28. 28 Causality: Interventions | Part A
  29. 29 Causality: Interventions | Part B
  30. 30 Causality: Counterfactuals | Part A
  31. 31 Causality: Counterfactuals | Part B
  32. 32 15a. Causality I
  33. 33 15b. Causality II
  34. 34 16. Sensitivity Analysis (Chapter 16)
  35. 35 17a. Reasoning about Classifiers
  36. 36 17b. Explaining Classifiers

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