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» Complexity of Inference in Graphical Models
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124
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NIPS
2004
15 years 3 months ago
Validity Estimates for Loopy Belief Propagation on Binary Real-world Networks
We introduce a computationally efficient method to estimate the validity of the BP method as a function of graph topology, the connectivity strength, frustration and network size....
Joris M. Mooij, Hilbert J. Kappen
124
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IJDMB
2008
105views more  IJDMB 2008»
15 years 2 months ago
Temporal representation for gene networks: towards a qualitative temporal data mining
: Recently lots of studies aim at modeling and inferring gene networks. Modeling tools propose graphical models having almost nothing about time description of events and regards t...
Nicolas Turenne, Sylviane R. Schwer
134
Voted
ICRA
2009
IEEE
188views Robotics» more  ICRA 2009»
15 years 7 days ago
Onboard contextual classification of 3-D point clouds with learned high-order Markov Random Fields
Contextual reasoning through graphical models such as Markov Random Fields often show superior performance against local classifiers in many domains. Unfortunately, this performanc...
Daniel Munoz, Nicolas Vandapel, Martial Hebert
145
Voted
JMLR
2012
13 years 5 months ago
Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data
We propose a novel mixtures of Gaussian processes model in which the gating function is interconnected with a probabilistic logical model, in our case Markov logic networks. In th...
Martin Schiegg, Marion Neumann, Kristian Kersting
136
Voted
PG
2000
IEEE
15 years 6 months ago
Rendering Natural Waters
Creating and rendering realistic water is one of the most daunting tasks in computer graphics. Realistic rendering of water requires that the sunlight and skylight illumination ar...
Simon Premoze, Michael Ashikhmin