Causal Markov condition

The Markov condition (sometimes called Markov assumption) for a Bayesian network states that any node in a Bayesian network is conditionally… (More)
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Topic mentions per year

1995-2016
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2010
2010
The causal Markov condition (CMC) is a postulate that links observations to causality. It describes the conditional independences… (More)
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Highly Cited
2010
Highly Cited
2010
Inferring the causal structure that links n observables is usually based upon detecting statistical dependences and choosing… (More)
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2007
2007
It is still a matter of controversy whether the Principle of the Common Cause (PCC) can be used as a basis for sound… (More)
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2006
2006
Hausman & Woodward present an argument for the Causal Markov Condition (CMC) on the basis of a principle they dub ‘modularity… (More)
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2006
2006
Daniel Hausman and James Woodward claim to prove that the causal Markov condition, so important to Bayes-nets methods for causal… (More)
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Highly Cited
2006
Highly Cited
2006
Most causal discovery algorithms in the literature exploit an assumption usually referred to as the Causal Faithfulness or… (More)
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2005
2005
The causal Markov condition (CMC) plays an important role in much recent work on the problem of causal inference from statistical… (More)
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2005
2005
This paper explores the relationship between a manipulability conception of causation and the causal Markov condition (CM). We… (More)
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Highly Cited
2000
Highly Cited
2000
This essay explains what the Causal Markov Condition says and defends the condition from the many criticisms that have been… (More)
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1996
1996
This paper provides <i>a priori</i> cirteria for determing when a causal model is sufficiently complete to be considered a… (More)
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