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JCB
2006
91views more  JCB 2006»
13 years 7 months ago
Reverse Engineering Discrete Dynamical Systems from Data Sets with Random Input Vectors
Recently a new algorithm for reverse engineering of biochemical networks was developed by Laubenbacher and Stigler. It is based on methods from computational algebra and finds mos...
Winfried Just
PE
2010
Springer
170views Optimization» more  PE 2010»
13 years 6 months ago
Approximating passage time distributions in queueing models by Bayesian expansion
We introduce Bayesian Expansion (BE), an approximate numerical technique for passage time distribution analysis in queueing networks. BE uses a class of Bayesian networks to appro...
Giuliano Casale
SMC
2007
IEEE
224views Control Systems» more  SMC 2007»
14 years 1 months ago
Complex networks as control paradigm for complex systems
—Rooted in a deep understanding of their major properties, a control paradigm for complex systems is proposed based on latest advances in modeling the dynamics of complex network...
Stefan Grobbelaar, Mihaela Ulieru
NIPS
2004
13 years 9 months ago
Dynamic Bayesian Networks for Brain-Computer Interfaces
We describe an approach to building brain-computer interfaces (BCI) based on graphical models for probabilistic inference and learning. We show how a dynamic Bayesian network (DBN...
Pradeep Shenoy, Rajesh P. N. Rao
CORR
2010
Springer
188views Education» more  CORR 2010»
13 years 7 months ago
A physically-based particle model of emergent crowd behaviors
This paper presents a modeling process in order to produce a realistic simulation of crowds in the ancient Greek agora of Argos. This place was a social theater in which two kinds...
Laure Heïgéas, Annie Luciani, Joë...