10 citations · 19 across the 4 of their papers we have counts for
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cs.NE2017★ 10 cited
A wake-sleep algorithm for recurrent, spiking neural networks
Johannes Thiele, Peter Diehl, Matthew Cook
We investigate a recently proposed model for cortical computation which performs relational inference. It consists of several interconnected, structurally equivalent populations of…
cs.NE2016★ 8 cited
Learning and Inferring Relations in Cortical Networks
Peter U. Diehl, Matthew Cook
A pressing scientific challenge is to understand how brains work. Of particular interest is the neocortex,the part of the brain that is especially large in humans, capable of handl…
cs.NE2016
Conversion of Artificial Recurrent Neural Networks to Spiking Neural Networks for Low-power Neuromorphic Hardware
Peter U. Diehl, Guido Zarrella, Andrew Cassidy +2
In recent years the field of neuromorphic low-power systems that consume orders of magnitude less power gained significant momentum. However, their wider use is still hindered by t…