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BMCBI
2010
229views more  BMCBI 2010»
13 years 10 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
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...
Martin Paluszewski, Thomas Hamelryck
AI
2009
Springer
14 years 4 months ago
Grid-Enabled Adaptive Metamodeling and Active Learning for Computer Based Design
Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...
Dirk Gorissen
ECML
2004
Springer
14 years 3 months ago
SWITCH: A Novel Approach to Ensemble Learning for Heterogeneous Data
The standard framework of machine learning problems assumes that the available data is independent and identically distributed (i.i.d.). However, in some applications such as image...
Rong Jin, Huan Liu
ATVA
2008
Springer
131views Hardware» more  ATVA 2008»
14 years 3 days ago
Computation Tree Regular Logic for Genetic Regulatory Networks
Model checking has proven to be a useful analysis technique not only for concurrent systems, but also for the genetic regulatory networks (Grns) that govern the functioning of livi...
Radu Mateescu, Pedro T. Monteiro, Estelle Dumas, H...
PE
2006
Springer
107views Optimization» more  PE 2006»
13 years 10 months ago
Efficient steady-state analysis of second-order fluid stochastic Petri nets
This paper presents an efficient solution technique for the steady-state analysis of the second-order Stochastic Fluid Model underlying a second-order Fluid Stochastic Petri Net (...
Marco Gribaudo, Rossano Gaeta