Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks

BACKGROUND: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distributions, including distributions from directional statistics (the statistics of angles, directions and orientations). RESULT...

Descripción completa

Detalles Bibliográficos
Autores principales: Paluszewski, Martin, Hamelryck, Thomas
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Software
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2848649/
https://www.ncbi.nlm.nih.gov/pubmed/20226024
http://dx.doi.org/10.1186/1471-2105-11-126

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2848649/
https://www.ncbi.nlm.nih.gov/pubmed/20226024
http://dx.doi.org/10.1186/1471-2105-11-126

Ejemplares similares