| ISBN: | 9783319530697 |
| Publication date: | 12th May 2017 |
| Author: | Demian Battaglia |
| Publisher: | Springer an imprint of Springer International Publishing |
| Format: | Hardback |
| Pagination: | 117 pages |
| Series: | The Springer Series on Challenges in Machine Learning |
| Genres: |
Artificial intelligence Computer vision |
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.
Neural Connectomics Challenge features in the following genres: Artificial intelligence, Computer vision
Hardback. Not Available.
Neural Connectomics Challenge was written by Demian Battaglia and published by Springer an imprint of Springer International Publishing
Neural Connectomics Challenge has 117 pages
Yes it is part of The Springer Series on Challenges in Machine Learning series