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» Complexity of Inference in Graphical Models
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BMCBI
2005
169views more  BMCBI 2005»
13 years 7 months ago
Genetic interaction motif finding by expectation maximization - a novel statistical model for inferring gene modules from synthe
Background: Synthetic lethality experiments identify pairs of genes with complementary function. More direct functional associations (for example greater probability of membership...
Yan Qi 0003, Ping Ye, Joel S. Bader
SCVMA
2004
Springer
14 years 1 months ago
A Generative Model of Dense Optical Flow in Layers
We introduce a generative model of dense flow fields within a layered representation of 3-dimensional scenes. Using probabilistic inference and learning techniques (namely, varia...
Anitha Kannan, Brendan J. Frey, Nebojsa Jojic
ICML
2009
IEEE
14 years 8 months ago
Large-scale deep unsupervised learning using graphics processors
The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free paramete...
Rajat Raina, Anand Madhavan, Andrew Y. Ng
ICCMS
2009
118views more  ICCMS 2009»
13 years 5 months ago
Optimized Parallel Implementation of Gillespie's First Reaction Method on Graphics Processing Units
The simulation of chemical reacting systems is one of the most challenging topics in Systems Biology, due to their complexity and inherent randomness. The Gillespie's Stochas...
Cristian Dittamo, Davide Cangelosi
JCP
2008
133views more  JCP 2008»
13 years 7 months ago
YAVISTA: A Graphical Tool for Comparing 802.11 Simulators
The difficulty to compare network simulators is a major obstacle to the broader adoption of these tools. This problem particularly affects 802.11 simulators because the 802.11 prot...
Ryad Ben-El-Kezadri, Farouk Kamoun