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AAAI
2011
13 years 11 months ago
Controlling Selection Bias in Causal Inference
Selection bias, caused by preferential exclusion of samples from the data, is a major obstacle to valid causal and statistical inferences; it cannot be removed by randomized exper...
Elias Bareinboim, Judea Pearl
CORR
2010
Springer
154views Education» more  CORR 2010»
14 years 11 months ago
Causal Markov condition for submodular information measures
The causal Markov condition (CMC) is a postulate that links observations to causality. It describes the conditional independences among the observations that are entailed by a cau...
Bastian Steudel, Dominik Janzing, Bernhard Sch&oum...
ISCI
2008
137views more  ISCI 2008»
14 years 11 months ago
Inference of differential equation models by genetic programming
This paper describes an evolutionary method for identifying a causal model from the observed time series data. We use a system of ordinary differential equations (ODEs) as the cau...
Hitoshi Iba
UAI
1993
15 years 1 months ago
Causal Independence for Knowledge Acquisition and Inference
I introduce a temporal belief-network representation of causal independence that a knowledge engineer can use to elicit probabilistic models. Like the current, atemporal belief-ne...
David Heckerman
METMBS
2003
255views Mathematics» more  METMBS 2003»
15 years 1 months ago
Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical Discovery
Causal Probabilistic Networks (CPNs), (a.k.a. Bayesian Networks, or Belief Networks) are well-established representations in biomedical applications such as decision support system...
Constantin F. Aliferis, Ioannis Tsamardinos, Alexa...