Accelerated Physical Emulation of Bayesian Inference in Spiking Neural Networks-Reference-Cited by-同舟云学术

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Accelerated Physical Emulation of Bayesian Inference in Spiking Neural Networks

Published:2019-11-14 Issue: Volume:13 Page:
ISSN:1662-453X
Container-title:Frontiers in Neuroscience
language:
Short-container-title:Front. Neurosci.

Author:

Kungl Akos F.,Schmitt Sebastian,Klähn Johann,Müller Paul,Baumbach Andreas,Dold Dominik,Kugele Alexander,Müller Eric,Koke Christoph,Kleider Mitja,Mauch Christian,Breitwieser Oliver,Leng Luziwei,Gürtler Nico,Güttler Maurice,Husmann Dan,Husmann Kai,Hartel Andreas,Karasenko Vitali,Grübl Andreas,Schemmel Johannes,Meier Karlheinz,Petrovici Mihai A.

Funder

Seventh Framework Programme

Horizon 2020

Heidelberg Graduate School of Fundamental Physics

Publisher

Frontiers Media SA

Subject

General Neuroscience

Reference74 articles.

1. A highly tunable 65-nm cmos lif neuron for a large scale neuromorphic system;Aamir,2016

2. The hamiltonian brain: efficient probabilistic inference with excitatory-inhibitory neural circuit dynamics;Aitchison;PLoS Comput. Biol.,2016

3. Truenorth: design and tool flow of a 65 mw 1 million neuron programmable neurosynaptic chip;Akopyan;IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.,2015

4. Affect-expressive movement generation with factored conditional restricted Boltzmann machines;Alemi,2015

5. Better mixing via deep representations;Bengio,2013

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