Neural Connectomics by Demian Battaglia-P2P
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,

Neural Connectomics Challenge (The Springer Series on Challenges in Machine Learning) by Demian Battaglia, Isabelle Guyon, Vincent Lemaire, Javier Orlandi, Bisakha Ray, Jordi Soriano-P2P
English | 117 pages | ePUB | 3.9 MB
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Neural Connectomics Challenge (The Springer Series on Challenges in Machine Learning) by Demian Battaglia, Isabelle Guyon, Vincent Lemaire, Javier Orlandi, Bisakha Ray, Jordi Soriano
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Neural Connectomics by Demian Battaglia-P2P
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