There is a PMRG mail list for those involved. Please mail email@example.com to join
or leave. Mail can be distributed to members using firstname.lastname@example.org.
There are many Web resources available to probabilistic modellers. The
following few pointers might be helpful
Association for Uncertainty in Artificial
in AI Course
An outline of Bayesian methods with some information on the
junction tree algorithm.
Jordan, M.I, Ghahramani, Z., Jaakkola, T.S., and Saul, L.K. (1998) An
variational methods for graphical models.
This paper also has an introduction with
an outline of the junction tree method.
Kalman filters are a common and fast probabilistic model for real
valued sequences. The following Kalman filter
website has a number of good resources.
For a good introduction to probabilistic graphical models see:
Castillo E., J. M. Gutierrez and A. S. Hadi (1997) Expert Systems and
Probabilistic Network Models. Springer.
Unfortunately Edinburgh University Library does not appear to stock
this book. It can be ordered from bookshops at 37.50 pounds sterling.