- (Neal, 1993) ⇒ Radford M. Neal. (1993). “Probabilistic Inference Using Markov Chain Monte Carlo Methods." Department of Computer Science, University of Toronto Toronto, CA.
Probabilistic inference is an attractive approach to uncertain reasoning and empirical learning in artificial intelligence. Computational difculties arise, however, because probabilistic models with the necessary realism and flexibility lead to complex distributions over high-dimensional spaces. Related problems in other fields have been tackled using Monte Carlo methods based on sampling using Markov chains, providing a rich array of techniques that can be applied to problems in artificial...
|1993 ProbabilisticInferenceUsingMark||Radford M. Neal||Probabilistic Inference Using Markov Chain Monte Carlo Methods||1993|