This quarter we will have several very interesting outside speakers, with medical and biological applications (David Baker, Virkam Chalana and David Haynor). There will be (overlapping) focuses on:
|January 16||Danny Walsh||Detecting regularity embedded in noise in spatial point patterns using partial Bayes factors based on K-functions|
|January 23||Adrian Raftery||Approximate Bayes factors for the number of components in a finite mixture|
|January 30||David Baker, UW Biochemistry||Using mixture models to classify aminoacid sequences|
|February 6||Vikram Chalana, MathSoft Inc.||Medical imaging and segmentation software developments (perhaps with a demo)|
|February 13||Thomas Richardson||How should we interpret the structure of a graphical model?|
|February 20||Chris Fraley||Model-based clustering using EM and Bayesian model selection: Applications to astronomy and real-time imaging|
|February 27||Derek Stanford||Determining the number of features in an image using approximate Bayes factors|
|March 6||David Haynor, UW Medical Center||Problems in medical imaging|
|March 13||Simon Byers||Clusterwise regression via mixture models|
Click here to return to Adrian Raftery's home page.
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