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» Explaining inferences in Bayesian networks
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BMCBI
2010
103views more  BMCBI 2010»
13 years 7 months ago
A method of predicting changes in human gene splicing induced by genetic variants in context of cis-acting elements
Background: Polymorphic variants and mutations disrupting canonical splicing isoforms are among the leading causes of human hereditary disorders. While there is a substantial evid...
Alexander G. Churbanov, Igor Vorechovsky, Chindo H...
ICCV
2007
IEEE
14 years 9 months ago
Supervised Learning of Image Restoration with Convolutional Networks
Convolutional networks have achieved a great deal of success in high-level vision problems such as object recognition. Here we show that they can also be used as a general method ...
Viren Jain, Joseph F. Murray, Fabian Roth, Sriniva...
DCOSS
2007
Springer
14 years 1 months ago
Separating the Wheat from the Chaff: Practical Anomaly Detection Schemes in Ecological Applications of Distributed Sensor Networ
Abstract. We develop a practical, distributed algorithm to detect events, identify measurement errors, and infer missing readings in ecological applications of wireless sensor netw...
Luís M. A. Bettencourt, Aric A. Hagberg, Le...
CVPR
2007
IEEE
14 years 9 months ago
Leveraging temporal, contextual and ordering constraints for recognizing complex activities in video
We present a scalable approach to recognizing and describing complex activities in video sequences. We are interested in long-term, sequential activities that may have several par...
Benjamin Laxton, Jongwoo Lim, David J. Kriegman
ECCV
2006
Springer
14 years 9 months ago
Learning Nonlinear Manifolds from Time Series
Abstract. There has been growing interest in developing nonlinear dimensionality reduction algorithms for vision applications. Although progress has been made in recent years, conv...
Ruei-Sung Lin, Che-Bin Liu, Ming-Hsuan Yang, Naren...