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Volume 30, Issue 8

August 2018

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ISSN 0899-7667

EISSN 1530-888X

In this Issue

Article
Letters

Article

Machine Learning: Deepest Learning as Statistical Data Assimilation Problems

Henry D. I. Abarbanel, Paul J. Rozdeba, Sasha Shirman

Neural Computation (2018) 30 (8): 2025–2055.

Abstract

View articletitled, Machine Learning: Deepest Learning as Statistical Data Assimilation Problems

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Letters

Optimal Decoding of Dynamic Stimuli by Heterogeneous Populations of Spiking Neurons: A Closed-Form Approximation

Yuval Harel, Ron Meir, Manfred Opper

Neural Computation (2018) 30 (8): 2056–2112.

Abstract

View articletitled, Optimal Decoding of Dynamic Stimuli by Heterogeneous Populations of Spiking Neurons: A Closed-Form Approximation

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Neural Simpletrons: Learning in the Limit of Few Labels with Directed Generative Networks

Dennis Forster, Abdul-Saboor Sheikh, Jörg Lücke

Neural Computation (2018) 30 (8): 2113–2174.

Abstract

View articletitled, Neural Simpletrons: Learning in the Limit of Few Labels with Directed Generative Networks

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Methods for Assessment of Memory Reactivation

Shizhao Liu, Andres D. Grosmark, Zhe Chen

Neural Computation (2018) 30 (8): 2175–2209.

Abstract

View articletitled, Methods for Assessment of Memory Reactivation

Supplementary data

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Evidence of Rentian Scaling of Functional Modules in Diverse Biological Networks

Javier J. How, Saket Navlakha

Neural Computation (2018) 30 (8): 2210–2244.

Abstract

View articletitled, Evidence of Rentian Scaling of Functional Modules in Diverse Biological Networks

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A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression

Michiel Stock, Tapio Pahikkala, Antti Airola, Bernard De Baets, Willem Waegeman

Neural Computation (2018) 30 (8): 2245–2283.

Abstract

View articletitled, A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression

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Confounder Detection in High-Dimensional Linear Models Using First Moments of Spectral Measures

Furui Liu, Laiwan Chan

Neural Computation (2018) 30 (8): 2284–2318.

Abstract

View articletitled, Confounder Detection in High-Dimensional Linear Models Using First Moments of Spectral Measures

Article

Machine Learning: Deepest Learning as Statistical Data Assimilation Problems

Letters

Optimal Decoding of Dynamic Stimuli by Heterogeneous Populations of Spiking Neurons: A Closed-Form Approximation

Neural Simpletrons: Learning in the Limit of Few Labels with Directed Generative Networks

Methods for Assessment of Memory Reactivation

Evidence of Rentian Scaling of Functional Modules in Diverse Biological Networks

A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression

Confounder Detection in High-Dimensional Linear Models Using First Moments of Spectral Measures

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Issues

Cover Image

Article

Machine Learning: Deepest Learning as Statistical Data Assimilation Problems

Letters

Optimal Decoding of Dynamic Stimuli by Heterogeneous Populations of Spiking Neurons: A Closed-Form Approximation

Neural Simpletrons: Learning in the Limit of Few Labels with Directed Generative Networks

Methods for Assessment of Memory Reactivation

Evidence of Rentian Scaling of Functional Modules in Diverse Biological Networks

A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression

Confounder Detection in High-Dimensional Linear Models Using First Moments of Spectral Measures

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