AbstractWe study the algebraic varieties defined by the conditional independence statements of Bayesian networks. A complete algebraic classification is given for Bayesian networks on at most five random variables. Hidden variables are related to the geometry of higher secant varieties
We recall the basic idea of an algebraic ap-proach to learning Bayesian network (BN) structure, name...
AbstractWe recall the basic idea of an algebraic approach to learning Bayesian network (BN) structur...
We study the Spohn conditional independence (CI) varieties of an $n$-player game for one-edge Bayesi...
AbstractWe study the algebraic varieties defined by the conditional independence statements of Bayes...
AbstractConditional independence models in the Gaussian case are algebraic varieties in the cone of ...
This dissertation studies the algebraic varieties arising from the conditional independence statemen...
We develop the necessary theory in computational algebraic geometry to place Bayesian networks into ...
AbstractConditional independence models in the Gaussian case are algebraic varieties in the cone of ...
AbstractIn this paper we demonstrate how Gröbner bases and other algebraic techniques can be used to...
Multinomial Bayesian networks with hidden variables are real algebraic varieties. Thus, they are the...
The purpose of this paper is to present a systematic way of analysing the geometry of the probabilit...
In this paper we demonstrate how Grobner bases and other algebraic techniques can be used to explore...
AbstractIn this paper we demonstrate how Gröbner bases and other algebraic techniques can be used to...
The paper investigates the construction of a joint graph as a global structure of network based on ...
Abstract. The present paper addresses the issue of learning the underlying structure of a discrete b...
We recall the basic idea of an algebraic ap-proach to learning Bayesian network (BN) structure, name...
AbstractWe recall the basic idea of an algebraic approach to learning Bayesian network (BN) structur...
We study the Spohn conditional independence (CI) varieties of an $n$-player game for one-edge Bayesi...
AbstractWe study the algebraic varieties defined by the conditional independence statements of Bayes...
AbstractConditional independence models in the Gaussian case are algebraic varieties in the cone of ...
This dissertation studies the algebraic varieties arising from the conditional independence statemen...
We develop the necessary theory in computational algebraic geometry to place Bayesian networks into ...
AbstractConditional independence models in the Gaussian case are algebraic varieties in the cone of ...
AbstractIn this paper we demonstrate how Gröbner bases and other algebraic techniques can be used to...
Multinomial Bayesian networks with hidden variables are real algebraic varieties. Thus, they are the...
The purpose of this paper is to present a systematic way of analysing the geometry of the probabilit...
In this paper we demonstrate how Grobner bases and other algebraic techniques can be used to explore...
AbstractIn this paper we demonstrate how Gröbner bases and other algebraic techniques can be used to...
The paper investigates the construction of a joint graph as a global structure of network based on ...
Abstract. The present paper addresses the issue of learning the underlying structure of a discrete b...
We recall the basic idea of an algebraic ap-proach to learning Bayesian network (BN) structure, name...
AbstractWe recall the basic idea of an algebraic approach to learning Bayesian network (BN) structur...
We study the Spohn conditional independence (CI) varieties of an $n$-player game for one-edge Bayesi...
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