Hidden Bibliographic Details
Other authors / contributors: | Battaglia, Demian.
Guyon, Isabelle, editor of compilation.
Lemaire, Vincent, editor of compilation.
Orlandi, Javier, editor of compilation.
Ray, Bisakha, editor of compilation.
Soriano, Jordi, editor of compilation.
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ISBN: | 9783319530703 3319530704 9783319530697 3319530690
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Digital file characteristics: | text file PDF
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Notes: | Includes bibliographical references. Print version record.
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Summary: | 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. |
Other form: | Print version: Neural connectomics challenge. Cham : Springer, 2017 3319530690 9783319530697
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Standard no.: | 10.1007/978-3-319-53070-3
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