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BIBE
2008
IEEE
111views Bioinformatics» more  BIBE 2008»
13 years 10 months ago
Structure learning for biomolecular pathways containing cycles
Bayesian network structure learning is a useful tool for elucidation of regulatory structures of biomolecular pathways. The approach however is limited by its acyclicity constraint...
S. Itani, Karen Sachs, Garry P. Nolan, M. A. Dahle...
ETFA
2008
IEEE
13 years 9 months ago
Efficient failure-free foundry production
Microshrinkages are known as probably the most difficult defects to avoid in high-precission foundry. Depending on the magnitude of this defect, the piece in which it appears must...
Yoseba K. Penya, Pablo Garcia Bringas, Argoitz Zab...
ECAI
2010
Springer
13 years 9 months ago
Probabilistic Logic with Conditional Independence Formulae
We investigate probabilistic propositional logic as a way of expressing and reasoning about uncertainty. In contrast to Bayesian networks, a logical approach can easily cope with i...
Magdalena Ivanovska, Martin Giese
PRL
2006
129views more  PRL 2006»
13 years 7 months ago
Learning spatial relations in object recognition
This paper studies two types of spatial relationships that can be learned from training examples for object recognition. The first one employs deformable relationships between obj...
Thang V. Pham, Arnold W. M. Smeulders
IPMU
2010
Springer
13 years 6 months ago
Approximation of Data by Decomposable Belief Models
It is well known that among all probabilistic graphical Markov models the class of decomposable models is the most advantageous in the sense that the respective distributions can b...
Radim Jirousek