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Stochastic logic programs: Sampling, inference and applications
James Cussens
Department of Computer Science
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Dive into the research topics of 'Stochastic logic programs: Sampling, inference and applications'. Together they form a unique fingerprint.
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Earth and Planetary Sciences
Algorithms
50%
Elimination
25%
Inference
100%
Machine Learning
25%
Markov Chain
25%
Sample
25%
Sampling
100%
Show
25%
Utilization
100%
Computer Science
Algorithms
50%
Application
100%
Explicit Representation
25%
Importance Sampling
25%
Machine Learning
25%
Markov Chain
25%
Posterior Distribution
25%
Programs
100%
Statistics
25%
Variable Elimination
25%
Mathematics
Approximates
25%
Importance Sampling
25%
Inference
100%
Markov Chain
25%
Metropolis-Hasting Algorithm
25%
Net Structure
25%
Posterior Distribution
25%
Samples
25%
Statistics
25%
Physics
Algorithms
25%
Machine Learning
25%
Sampling
100%
Utilization
100%
Work
25%
Economics, Econometrics and Finance
Labour
25%
Machine Learning
25%
Markov Chain
25%