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» Causal inference using the algorithmic Markov condition
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BMEI
2008
IEEE
15 years 4 months ago
Using Phylogenetic Relationships to Improve the Inference of Transcriptional Regulatory Networks
Inferring transcriptional regulatory networks from geneexpression data remains a challenging problem, in part because of the noisy nature of the data and the lack of strong networ...
Xiuwei Zhang, Maryam Zaheri, Bernard M. E. Moret
DMSN
2008
ACM
14 years 11 months ago
Probabilistic processing of interval-valued sensor data
When dealing with sensors with different time resolutions, it is desirable to model a sensor reading as pertaining to a time interval rather than a unit of time. We introduce two ...
Sander Evers, Maarten M. Fokkinga, Peter M. G. Ape...
IJCAI
2001
14 years 11 months ago
Approximate inference for first-order probabilistic languages
A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...
Hanna Pasula, Stuart J. Russell
ICIP
2002
IEEE
15 years 11 months ago
Unsupervised detection of contours using a statistical model
In this paper, we describe an unsupervised segmentation method for contours which proves quite adapted for the images obtained by electronic acquisition. We present two statistica...
François Destrempes, Max Mignotte
BMCBI
2005
134views more  BMCBI 2005»
14 years 9 months ago
Ancestral sequence alignment under optimal conditions
Background: Multiple genome alignment is an important problem in bioinformatics. An important subproblem used by many multiple alignment approaches is that of aligning two multipl...
Alexander K. Hudek, Daniel G. Brown 0001