Introduction To Bayesian Inference
author:
Christopher Bishop,
Microsoft Research
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| Slides | |
| 0:00 | INTRODUCTION TOBAYESIAN INFERENCE –PART 1 |
| 1:00 | Please ask questions |
| 1:24 | Research |
| 1:34 | First Generation |
| 3:13 | Second Generation |
| 4:02 | Third Generation |
| 5:37 | Probability Theory |
| 6:43 | The Rules of Probability |
| 7:12 | Bayes’ Theorem |
| 7:54 | Oranges and Apples |
| 9:41 | Probability Densities |
| 10:33 | Bayesian Inference |
| 13:14 | Why is prior knowledge important? |
| 15:10 | Probabilistic Graphical Models |
| 17:30 | Decomposition |
| 19:16 | Directed Graphs |
| 24:29 | MAAS |
| 25:56 | Graph - 1 |
| 27:35 | Graph - 2 |
| 29:55 | Graph - 3 |
| 31:36 | Graph - 4 |
| 33:18 | Factor Graphs |
| 34:10 | From Directed Graph to Factor Graph |
| 34:51 | Inference on Graphs |
| 35:48 | Factor Trees: Separation |
| 40:05 | Messages: From Factors To Variables |
| 41:05 | Messages: From Variables To Factors |
| 46:30 | What if the graph is not a tree? |
| 47:02 | What if marginalisations are not tractable? |
| 49:14 | Illustration: Bayesian Ranking |
| 50:58 | Two Player Match Outcome Model |
| 53:44 | Two Team Match Outcome Model |
| 54:33 | Multiple Team Match Outcome Model |
| 54:44 | Graph - 5 |
| 56:00 | Graph - 6 |
| 57:57 | Skill Dynamics |
| 62:50 | TrueSkillTM |
| 65:04 | Graph - 7 |
| 66:57 | infer.net |
| 67:32 | Infer.Net demonstration |
| 67:41 | Graph - 8 |
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I liked the slides on binary variable - distribution of placeba/Treated relationship of drugs. The question is: how can it be further studied and quantified to be made a standard measure to treat patients?
this is really good 4 me....