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AAAI
2007
13 years 10 months ago
Probabilistic Community Discovery Using Hierarchical Latent Gaussian Mixture Model
Complex networks exist in a wide array of diverse domains, ranging from biology, sociology, and computer science. These real-world networks, while disparate in nature, often compr...
Haizheng Zhang, C. Lee Giles, Henry C. Foley, John...
ICONIP
2007
13 years 9 months ago
Discovery of Linear Non-Gaussian Acyclic Models in the Presence of Latent Classes
Abstract. An effective way to examine causality is to conduct an experiment with random assignment. However, in many cases it is impossible or too expensive to perform controlled ...
Shohei Shimizu, Aapo Hyvärinen
CVPR
2011
IEEE
12 years 11 months ago
Nonlinear Shape Manifolds as Shape Priors in Level Set Segmentation and Tracking
We propose a novel nonlinear, probabilistic and variational method for adding shape information to level setbased segmentation and tracking. Unlike previous work, we represent sha...
Victor Prisacariu, Ian Reid
NIPS
2008
13 years 9 months ago
Efficient Sampling for Gaussian Process Inference using Control Variables
Sampling functions in Gaussian process (GP) models is challenging because of the highly correlated posterior distribution. We describe an efficient Markov chain Monte Carlo algori...
Michalis Titsias, Neil D. Lawrence, Magnus Rattray
BMCBI
2008
118views more  BMCBI 2008»
13 years 7 months ago
Inferring transcriptional compensation interactions in yeast via stepwise structure equation modeling
Background: With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few appro...
Grace S. Shieh, Chung-Ming Chen, Ching-Yun Yu, Jui...