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Neural connectomics challenge

Battaglia, Demian.

Neural connectomics challenge

Record Type:	Electronic resources : Monograph/item
Title/Author:	Neural connectomics challengeedited by Demian Battaglia ... [et al.].
other author:	Battaglia, Demian.
Published:	Cham :Springer International Publishing :2017.
Description:	x, 117 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Computational neuroscience.
Online resource:	http://dx.doi.org/10.1007/978-3-319-53070-3
ISBN:	9783319530703$q(electronic bk.)

Neural connectomics challenge
Neural connectomics challenge[electronic resource] /edited by Demian Battaglia ... [et al.]. - Cham :Springer International Publishing :2017. - x, 117 p. :ill., digital ;24 cm. - The Springer series on challenges in machine learning,2520-131X. - Springer series on challenges in machine learning..

First Connectomics Challenge: From Imaging to Connectivity -- Simple Connectome Inference from Partial Correlation Statistics in Calcium Imaging -- Supervised Neural Network Structure Recovery -- Signal Correlation Prediction Using Convolutional Neural Networks -- Reconstruction of Excitatory Neuronal Connectivity via Metric Score Pooling and Regularization -- Neural Connectivity Reconstruction from Calcium Imaging Signal using Random Forest with Topological Features -- Efficient Combination of Pairwise Feature Networks -- Predicting Spiking Activities in DLS Neurons with Linear-Nonlinear-Poisson Model -- SuperSlicing Frame Restoration for Anisotropic ssTEM and Video Data -- Supplemental Information.

ISBN: 9783319530703$q(electronic bk.)

Standard No.: 10.1007/978-3-319-53070-3doiSubjects--Topical Terms:

190429
Computational neuroscience.

LC Class. No.: QP357.5

Dewey Class. No.: 612.8

Neural connectomics challenge
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245 0 0 $a Neural connectomics challenge $h [electronic resource] / $c edited by Demian Battaglia ... [et al.].
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505 0 $a First Connectomics Challenge: From Imaging to Connectivity -- Simple Connectome Inference from Partial Correlation Statistics in Calcium Imaging -- Supervised Neural Network Structure Recovery -- Signal Correlation Prediction Using Convolutional Neural Networks -- Reconstruction of Excitatory Neuronal Connectivity via Metric Score Pooling and Regularization -- Neural Connectivity Reconstruction from Calcium Imaging Signal using Random Forest with Topological Features -- Efficient Combination of Pairwise Feature Networks -- Predicting Spiking Activities in DLS Neurons with Linear-Nonlinear-Poisson Model -- SuperSlicing Frame Restoration for Anisotropic ssTEM and Video Data -- Supplemental Information.
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