Add to ORKGPaper presented at Strathmore International Math Research Conference on July 23 - 27, 2012Paper presented at Strathmore International Mathematics Research Conference on July 23 - 27, 201
We describe how to combine probabilistic logic and Bayesian networks to obtain a new frame-work ("Ba...
Bayesian networks are a very general and powerful tool that can be used for a large number of proble...
Bayesian networks provide an elegant formalism for representing and reasoning about uncertainty usin...
Tutorial tenuto al 58th Annual Reliability and Maintainability Symposium (RAMS 2012
This tutorial provides an overview of Bayesian belief networks. The sub-ject is introduced through a...
A study of the possibility of casting plausible matheamtical inference in Bayesian terms
Bayesian Belief Networks are graph-based representations of probability distributions. In the last d...
The following full text is a preprint version which may differ from the publisher's version
This tutorial provides an overview of Bayesian belief networks. The sub-ject is introduced through a...
This book is an extension of the author’s first book and serves as a guide and manual on how to spec...
The analysis of nominal data is often reduced to accumulation and description. Bayesian methods offe...
Bayesian nets are widely used in artificial intelligence as a calculus for casual reasoning, enablin...
Delft Institute of Applied MathematicsElectrical Engineering, Mathematics and Computer Scienc
Contains fulltext : 94188.pdf (preprint version ) (Open Access
In the field of Artificial Intelligence, Bayesian Networks (BN) are a well-known framework for reaso...
We describe how to combine probabilistic logic and Bayesian networks to obtain a new frame-work ("Ba...
Bayesian networks are a very general and powerful tool that can be used for a large number of proble...
Bayesian networks provide an elegant formalism for representing and reasoning about uncertainty usin...
Tutorial tenuto al 58th Annual Reliability and Maintainability Symposium (RAMS 2012
This tutorial provides an overview of Bayesian belief networks. The sub-ject is introduced through a...
A study of the possibility of casting plausible matheamtical inference in Bayesian terms
Bayesian Belief Networks are graph-based representations of probability distributions. In the last d...
The following full text is a preprint version which may differ from the publisher's version
This tutorial provides an overview of Bayesian belief networks. The sub-ject is introduced through a...
This book is an extension of the author’s first book and serves as a guide and manual on how to spec...
The analysis of nominal data is often reduced to accumulation and description. Bayesian methods offe...
Bayesian nets are widely used in artificial intelligence as a calculus for casual reasoning, enablin...
Delft Institute of Applied MathematicsElectrical Engineering, Mathematics and Computer Scienc
Contains fulltext : 94188.pdf (preprint version ) (Open Access
In the field of Artificial Intelligence, Bayesian Networks (BN) are a well-known framework for reaso...
We describe how to combine probabilistic logic and Bayesian networks to obtain a new frame-work ("Ba...
Bayesian networks are a very general and powerful tool that can be used for a large number of proble...
Bayesian networks provide an elegant formalism for representing and reasoning about uncertainty usin...