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» A Probabilistic Approach to Marker Propagation
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BMCBI
2005
140views more  BMCBI 2005»
13 years 7 months ago
Dissecting systems-wide data using mixture models: application to identify affected cellular processes
Background: Functional analysis of data from genome-scale experiments, such as microarrays, requires an extensive selection of differentially expressed genes. Under many condition...
J. Peter Svensson, Renée X. de Menezes, Ing...
MCS
2005
Springer
14 years 1 months ago
Mixture of Gaussian Processes for Combining Multiple Modalities
This paper describes a unified approach, based on Gaussian Processes, for achieving sensor fusion under the problematic conditions of missing channels and noisy labels. Under the ...
Ashish Kapoor, Hyungil Ahn, Rosalind W. Picard
AI
2010
Springer
13 years 7 months ago
Understanding the scalability of Bayesian network inference using clique tree growth curves
Bayesian networks (BNs) are used to represent and ef ciently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to per...
Ole J. Mengshoel
SIGSOFT
2004
ACM
14 years 8 months ago
Reasoning about partial goal satisfaction for requirements and design engineering
Exploring alternative options is at the heart of the requirements and design processes. Different alternatives contribute to different degrees of achievement of non-functional goa...
Emmanuel Letier, Axel van Lamsweerde
29
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ICRA
2008
IEEE
144views Robotics» more  ICRA 2008»
14 years 1 months ago
Interacting multiple model monocular SLAM
— Recent work has demonstrated the benefits of adopting a fully probabilistic SLAM approach in sequential motion and structure estimation from an image sequence. Unlike standard...
Javier Civera, Andrew J. Davison, J. M. M. Montiel