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» Causal inference using the algorithmic Markov condition
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WSC
2008
15 years 2 days ago
Applying causal inference to understand emergent behavior
Emergent behaviors in simulations require explanation, so that valid behaviors can be separated from design or coding errors. Validation of emergent behavior requires accumulation...
Ross Gore, Paul F. Reynolds Jr.
BMCBI
2010
172views more  BMCBI 2010»
14 years 10 months ago
Comparison of evolutionary algorithms in gene regulatory network model inference
Background: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineeri...
Alina Sîrbu, Heather J. Ruskin, Martin Crane
ECAI
2004
Springer
15 years 3 months ago
Indirect and Conditional Sensing in the Event Calculus
Controlling the sensing of an environment by an agent has been accepted as necessary for effective operation within most practical domains. Usually, however, agents operate in par...
Jeremy Forth, Murray Shanahan
ICDM
2003
IEEE
158views Data Mining» more  ICDM 2003»
15 years 3 months ago
Identifying Markov Blankets with Decision Tree Induction
The Markov Blanket of a target variable is the minimum conditioning set of variables that makes the target independent of all other variables. Markov Blankets inform feature selec...
Lewis Frey, Douglas H. Fisher, Ioannis Tsamardinos...
ANSS
2006
IEEE
15 years 3 months ago
A New Approach for Computing Conditional Probabilities of General Stochastic Processes
In this paper Hidden Markov Model algorithms are considered as a method for computing conditional properties of continuous-time stochastic simulation models. The goal is to develo...
Fabian Wickborn, Claudia Isensee, Thomas Simon, Sa...