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IJAR
2002
102views more  IJAR 2002»
13 years 9 months ago
Networks of probabilistic events in discrete time
The usual methods of applying Bayesian networks to the modeling of temporal processes, such as Dean and Kanazawa's dynamic Bayesian networks (DBNs), consist in discretizing t...
Severino F. Galán, Francisco Javier D&iacut...
ICML
2005
IEEE
14 years 10 months ago
Learning first-order probabilistic models with combining rules
Many real-world domains exhibit rich relational structure and stochasticity and motivate the development of models that combine predicate logic with probabilities. These models de...
Sriraam Natarajan, Prasad Tadepalli, Eric Altendor...
WADS
1989
Springer
84views Algorithms» more  WADS 1989»
14 years 2 months ago
Skip Lists: A Probabilistic Alternative to Balanced Trees
rees can be used for representing abstract data types such as dictionaries and ordered lists. They work well when the elements are inserted in a random order. Some sequences of ope...
William Pugh
NIPS
2004
13 years 11 months ago
Probabilistic Computation in Spiking Populations
As animals interact with their environments, they must constantly update estimates about their states. Bayesian models combine prior probabilities, a dynamical model and sensory e...
Richard S. Zemel, Quentin J. M. Huys, Rama Nataraj...
BIOINFORMATICS
2006
118views more  BIOINFORMATICS 2006»
13 years 10 months ago
A probabilistic dynamical model for quantitative inference of the regulatory mechanism of transcription
Motivation Quantitative estimation of the regulatory relationship between transcription factors and genes is a fundamental stepping stone when trying to develop models of cellular...
Guido Sanguinetti, Magnus Rattray, Neil D. Lawrenc...