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Neural Connectomics Challenge (The Springer Series on Challenges in Machine Learning) - Hardcover
Book 1 of 8: The Springer Series on Challenges in Machine Learning
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.
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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.
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Neural Connectomics Challenge (The Springer Series on Challenges in Machine Learning)
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Neural Connectomics Challenge (eng)
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Neural Connectomics Challenge
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Berlin Springer International Publishing Springer Mai 2017, 2017
ISBN 10: 3319530690
ISBN 13: 9783319530697
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 117 pp. Englisch. Seller Inventory # 9783319530697
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Neural Connectomics Challenge
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Explains how machine learning tools have the capacity to predict the behavior or response of a complex systemOffers tools for the advancement of neuroscience through machine learning techniquesCombine. Seller Inventory # 135726380
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Neural Connectomics Challenge
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Springer, Berlin, Springer, 2017
ISBN 10: 3319530690
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9783319530697