Übersicht			Auf mobile öffnen

Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	Mai 2018
Genre:	EDV / Informatik
	Artificial Intelligence / B / causality / computer science / Computer Vision / Connectomes / Connectomics / Deep Learning / Image processing / Image Processing and Computer Vision / machine learning / Maschinelles Sehen, Bildverstehen / Network reconstruction / Neural connectomics / Optical data processing / Partial correlation / Time Series mehr...
ISBN:	9783319850542
EAN-Code:	9783319850542
Verlag:	Springer EN
Einband:	Kartoniert
Sprache:	English
Serie:	The Springer Series on Challenges in Machine Learning
Dimensionen:	H 235 mm / B 155 mm / D
Gewicht:	209 gr
Seiten:	117
Illustration:	X, 117 p. 28 illus., schwarz-weiss Illustrationen
Zus. Info:	EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

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.