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Ancestral graph

In statistics and Markov modeling, an ancestral graph is a type of mixed graph to provide a graphical representation for the result of marginalizing… Expand
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Papers overview

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2011
2011
Proof. As the edges in GC represent causal relations, a path of length 0 (no edge) is not considered a causal relation, and… Expand
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2010
2010
We present an algorithm name cSAT+ for learning the causal structure in a domain from datasets measuring different variable sets… Expand
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2009
2009
Marginal independence constraints play an important role in learning with graphical models. One way of parameterizing a model of… Expand
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Highly Cited
2008
Highly Cited
2008
  • Jiji Zhang
  • J. Mach. Learn. Res.
  • 2008
  • Corpus ID: 1901105
Causal reasoning is primarily concerned with what would happen to a system under external interventions. In particular, we are… Expand
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2008
2008
‘Iterative conditional fitting’ is a recently proposed algorithm that can be used for maximization of the likelihood function in… Expand
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2004
2004
Ancestral graph models, introduced by Richardson and Spirtes (2002), generalize both Markov random fields and Bayesian networks… Expand
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2004
2004
For an ancestral graph with four vertices, we show that the associated binary model exhibits different properties than the… Expand
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Highly Cited
2002
Highly Cited
2002
Abstract : This paper introduces a class of graphical independence models that is closed under marginalization and conditioning… Expand
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2002
2002
Ancestral graphs are a class of graphs that encode conditional independence relations arising in DAG models with latent and… Expand
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Highly Cited
1996
Highly Cited
1996
Directed acyclic graphs have been used fruitfully to represent causal structures (Pearl 1988). However, in the social sciences… Expand
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