I am working on an applied project involving intractable inference in
temporal Bayesian networks and influence diagrams. We are examining
a number of approximate methods. We have identified particle filters
as one of the approaches to investigate. We have found a number of
references, but they tend to be jargon-filled and require a lot of
background even to get started. I would very much like to find
something tutorial in nature that would be appropriate for someone
with a background in standard engineering math, a knowledge of basic
physics, an understanding of Bayesian networks at the applied user
level, but no specialized knowledge of statistical physics, advanced
statistics, or information theory. Does anyone know of any
references like this? If I can't find one, I'll write one, but it
would be nice if something existed.
Thanks very much!
Kathy Laskey
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