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KDD
2007
ACM
124views Data Mining» more  KDD 2007»
15 years 10 months ago
Hierarchical mixture models: a probabilistic analysis
Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...
Mark Sandler
BMCBI
2005
89views more  BMCBI 2005»
15 years 4 months ago
An empirical analysis of training protocols for probabilistic gene finders
Background: Generalized hidden Markov models (GHMMs) appear to be approaching acceptance as a de facto standard for state-of-the-art ab initio gene finding, as evidenced by the re...
William H. Majoros, Steven Salzberg
JCB
2006
185views more  JCB 2006»
15 years 4 months ago
A Probabilistic Methodology for Integrating Knowledge and Experiments on Biological Networks
Biological systems are traditionally studied by focusing on a specific subsystem, building an intuitive model for it, and refining the model using results from carefully designed ...
Irit Gat-Viks, Amos Tanay, Daniela Raijman, Ron Sh...
ICCV
2009
IEEE
16 years 7 months ago
Complete Multi-View Reconstruction of Dynamic Scenes from Probabilistic Fusion of Narrow and Wide Baseline Stereo
This paper presents a novel approach to achieve accurate and complete multi-view reconstruction of dynamic scenes (or 3D videos). 3D videos consist in sequences of 3D models in mot...
Tony Tung, Shohei Nobuhara, Takashi Matsuyama
BMCBI
2006
147views more  BMCBI 2006»
15 years 4 months ago
A hidden Markov model approach for determining expression from genomic tiling micro arrays
Background: Genomic tiling micro arrays have great potential for identifying previously undiscovered coding as well as non-coding transcription. To-date, however, analyses of thes...
Kasper Munch, Paul P. Gardner, Peter Arctander, An...