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Neural Connectomics Challenge (The Springer Series on Challenges in Machine Learning) - Tapa dura

Libro 1 de 8: The Springer Series on Challenges in Machine Learning
 
9783319530697: Neural Connectomics Challenge (The Springer Series on Challenges in Machine Learning)
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ISBN 10: 3319530690 ISBN 13: 9783319530697
Editorial: Springer, 2017

Sinopsis

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.
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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.


"Sinopsis" puede pertenecer a otra edición de este libro.

Reseña del editor

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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2017
Idioma
Inglés
ISBN 10 
3319530690
ISBN 13 
9783319530697
Encuadernación
Tapa dura
Número de páginas
117
Editor
Battaglia Demian, Guyon Isabelle, Lemaire Vincent, Orlandi Javier, Ray Bisakha, Soriano Jordi
Contacto del fabricante
no disponible
Persona responsable
no disponible