102 search results - page 13 / 21 » Gaussian Process Structural Equation Models with Latent Vari... |
NIPS
2008
13 years 9 months ago
2008
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
NIPS
1997
13 years 9 months ago
1997
We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...
HICSS
2005
IEEE
14 years 1 months ago
2005
IEEE
Measurement of organizational knowledge assets is necessary to determine the effectiveness of knowledge management initiatives. A Knowledge Management Capability Assessment instru...
UAI
2004
13 years 9 months ago
2004
Ancestral graph models, introduced by Richardson and Spirtes (2002), generalize both Markov random fields and Bayesian networks to a class of graphs with a global Markov property ...
ICDM
2008
IEEE
14 years 2 months ago
2008
IEEE
We introduce dynamic correlated topic models (DCTM) for analyzing discrete data over time. This model is inspired by the hierarchical Gaussian process latent variable models (GP-L...