604 search results - page 15 / 121 » Bayesian inference on biopolymer models |
AUSAI
1998
Springer
13 years 11 months ago
1998
Springer
Naive Bayesian classi ers utilise a simple mathematical model for induction. While it is known that the assumptions on which this model is based are frequently violated, the predic...
BMCBI
2010
13 years 7 months ago
2010
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
ACL
2010
13 years 5 months ago
2010
Learning a tree substitution grammar is very challenging due to derivational ambiguity. Our recent approach used a Bayesian non-parametric model to induce good derivations from tr...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian proces...
ICANN
2010
Springer
13 years 8 months ago
2010
Springer
With the term super-resolution we refer to the problem of reconstructing an image of higher resolution than that of unregistered and degraded observations. Typically, the reconstru...