Neural Connectomics Challenge - Couverture souple

Couverture souple

ISBN 10 : 3319850547 ISBN 13 : 9783319850542

Editeur : Springer, 2018

Synopsis

This book illustrates the thrust of the scientific community to use machine learning concepts for tackling a complex problem: given time series of neuronal spontaneous activity, which is the underlying connectivity between the neurons in the network? The contributing authors also develop tools for the advancement of neuroscience through machine learning techniques, with a focus on the major open problems in neuroscience.
While the techniques have been developed for a specific application, they address the more general problem of network reconstruction from observational time series, a problem of interest in a wide variety of domains, including econometrics, epidemiology, and climatology, to cite only a few.The book is designed for the mathematics, physics and computer science communities that carry out research in neuroscience problems. The content is also suitable for the machine learning community because it exemplifies how to approach the same problem from different perspectives.

Détails de l'édition

• Éditeur: Springer
• Date d'édition: 2018
• Langue: anglais
• ISBN 10: 3319850547
• ISBN 13: 9783319850542
• Reliure: Broché
• Nombre de pages: 128
• Éditeur: Battaglia Demian, Guyon Isabelle, Lemaire Vincent, Orlandi Javier, Ray Bisakha, Soriano Jordi
• Coordonnées du fabricant: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3,69115 Heidelberg, Germany; Heidelberg; 69115; Allemagne