31 search results - page 3 / 7 » Learning Dynamic Bayesian Networks from Multivariate Time Se... |
NIPS
2000
13 years 6 months ago
2000
Experimental data show that biological synapses behave quite differently from the symbolic synapses in common artificial neural network models. Biological synapses are dynamic, i....
ICML
2010
IEEE
13 years 3 months ago
2010
IEEE
Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with heterogeneity and non-stationarity in temporal processes. Various ap...
BMCBI
2005
13 years 5 months ago
2005
Background: Reconstructing regulatory networks from gene expression profiles is a challenging problem of functional genomics. In microarray studies the number of samples is often ...
IJON
2007
13 years 5 months ago
2007
We investigate a recently proposed method for the analysis of oscillatory patterns in EEG data, with respect to its capacity of further quantifying processes on slower (< 1 Hz)...
BMCBI
2006
13 years 5 months ago
2006
Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...