COMP6469 Introduction to Probabilistic Graphical Models
COMP6469 is only available under certain award programs.
| Offered By | Department of Computer Science |
|---|---|
| Academic Career | Graduate Coursework |
| Course Subject | Computer Science |
| Offered in | COMP6469 will not be offered in 2009 |
| Unit Value | 6 units |
| Course Description | Probabilistic graphical models give the structural aspects of a problem (including dependency, cause and relevance). This course provides a broad but thorough introduction to the methods and practice of probabilistic graphical models. Topics covered will include Bayesian inference and maximum likelihood modeling; undirected (Markov) and directed (Bayesian) graphical models and their analysis and properties; typical applications and graphical patterns used therein, variable elimination, probability computation, and optimisation. |
| Indicative Assessment | Two written assignments (30% each); Oral examination (40%) |
| Workload | 13 x 3 hour lectures` |
| Course Classification(s) | AdvancedAdvanced courses are designed for students having reached 'first degree' level of assumed knowledge, which provide a deep understanding of contemporary issues; or 'second degree' and higher levels of knowledge; or for transition to research training programs. |
| Areas of Interest | Computer Science |
| Requisite Statement | Enrolment in the MICT or approval by the program convenor |
| Recommended Courses | Some exposure to statistics |
| Consent Required | Consent is required prior to enrolling in this course. |
The information published on the Study at ANU 2009 website applies to the 2009 academic year only. All information provided on this website replaces the information contained in the Study at ANU 2008 website.
