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FGCN
2008
IEEE
155views Communications» more  FGCN 2008»
15 years 3 months ago
Modeling the Marginal Distribution of Gene Expression with Mixture Models
We report the results of fitting mixture models to the distribution of expression values for individual genes over a broad range of normal tissues, which we call the marginal expr...
Edward Wijaya, Hajime Harada, Paul Horton
JOT
2008
200views more  JOT 2008»
15 years 2 months ago
Applying Model Checking to Concurrent UML Models
We present, in this paper, a framework supporting a formal verification of concurrent UML models using the Maude language. We consider both static and dynamic features of concurre...
Patrice Gagnon, Farid Mokhati, Mourad Badri
IJON
2007
79views more  IJON 2007»
15 years 2 months ago
Predicting neuronal activity with simple models of the threshold type: Adaptive Exponential Integrate-and-Fire model with two co
An adaptive Exponential Integrate-and-Fire (aEIF) model was used to predict the activity of layer-V-pyramidal neurons of rat neocortex under random current injection. A new protoc...
Claudia Clopath, Renaud Jolivet, Alexander Rauch, ...
SIGPRO
2002
72views more  SIGPRO 2002»
15 years 1 months ago
Modeling electricity loads in California: ARMA models with hyperbolic noise
In this paper we address the issue of modeling and forecasting electricity loads. We apply a two-step procedure to a series of system-wide loads from the California power market. ...
J. Nowicka-Zagrajek, R. Weron
ICML
1999
IEEE
16 years 2 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox