Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Synergies between network-based representation and probabilistic graphical models for classification, inference and optimization problems in neurosciences
Year:2010
Research Areas
  • Artificial intelligence
Information
Abstract
Neural systems network-based representations are useful tools to analyze numerous phenomena in neuroscience. Probabilistic graphical models (PGMs) give a concise and still rich representation of complex systems from different domains, including neural systems. In this paper we analyze the characteristics of a bidirectional relationship between networks-based representations and PGMs. We show the way in which this relationship can be exploited introducing a number of methods for the solution of classification, inference and optimization problems. To illustrate the applicability of the introduced methods, a number of problems from the field of neuroscience, in which ongoing research is conducted, are used.
International
Si
Congress
23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010
960
Place
Córdoba, España
Reviewers
Si
ISBN/ISSN
3-642-13032-1
10.1007/978-3-642-13033-5_16
Start Date
01/06/2010
End Date
04/06/2010
From page
149
To page
158
Trends in Applied Intelligent Systems
Participants
  • Autor: Roberto Santana Hermida (UPM)
  • Autor: Maria Concepcion Bielza Lozoya (UPM)
  • Autor: Pedro Maria Larrañaga Mugica (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: COMPUTATIONAL INTELLIGENCE GROUP
  • Centro o Instituto I+D+i: Centro de tecnología Biomédica CTB
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