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» Causal Discovery from Changes
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KDD
2009
ACM
230views Data Mining» more  KDD 2009»
13 years 12 months ago
Grouped graphical Granger modeling methods for temporal causal modeling
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
JOCN
2010
99views more  JOCN 2010»
13 years 5 months ago
"Virus and Epidemic": Causal Knowledge Activates Prediction Error Circuitry
■ Knowledge about cause and effect relationships (e.g., virus– epidemic) is essential for predicting changes in the environment and for anticipating the consequences of events...
Daniela B. Fenker, Mircea Ariel Schoenfeld, Michae...
HUC
2010
Springer
13 years 7 months ago
Social sensing for epidemiological behavior change
An important question in behavioral epidemiology and public health is to understand how individual behavior is affected by illness and stress. Although changes in individual behav...
Anmol Madan, Manuel Cebrián, David Lazer, A...
DATAMINE
2006
117views more  DATAMINE 2006»
13 years 7 months ago
A Rule-Based Approach for Process Discovery: Dealing with Noise and Imbalance in Process Logs
Effective information systems require the existence of explicit process models. A completely specified process design needs to be developed in order to enact a given business proce...
Laura Maruster, A. J. M. M. Weijters, Wil M. P. va...
BMCBI
2011
13 years 2 months ago
Using Stochastic Causal Trees to Augment Bayesian Networks for Modeling eQTL Datasets
Background: The combination of genotypic and genome-wide expression data arising from segregating populations offers an unprecedented opportunity to model and dissect complex phen...
Kyle C. Chipman, Ambuj K. Singh