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ICML
2008
IEEE
14 years 9 months ago
Causal modelling combining instantaneous and lagged effects: an identifiable model based on non-Gaussianity
Causal analysis of continuous-valued variables typically uses either autoregressive models or linear Gaussian Bayesian networks with instantaneous effects. Estimation of Gaussian ...
Aapo Hyvärinen, Patrik O. Hoyer, Shohei Shimi...
CEC
2003
IEEE
14 years 14 days ago
Dynamics of gene expression in an artificial genome
Abstract- Complex systems techniques provide a powerful tool to study the emergent properties of networks of interacting genes. In this study we extract models of genetic regulator...
Kai Willadsen, Janet Wiles
IJAR
2010
130views more  IJAR 2010»
13 years 7 months ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki
BMCBI
2010
176views more  BMCBI 2010»
13 years 9 months ago
Bayesian statistical modelling of human protein interaction network incorporating protein disorder information
Background: We present a statistical method of analysis of biological networks based on the exponential random graph model, namely p2-model, as opposed to previous descriptive app...
Svetlana Bulashevska, Alla Bulashevska, Roland Eil...
AAAI
1998
13 years 10 months ago
Structured Representation of Complex Stochastic Systems
This paperconsidersthe problem of representingcomplex systems that evolve stochastically over time. Dynamic Bayesian networks provide a compact representation for stochastic proce...
Nir Friedman, Daphne Koller, Avi Pfeffer