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Peter U. Diehl
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2010 – 2019
- 2018
- [j3]Peter U. Diehl, Julien N. P. Martel, Jakob Buhmann, Matthew Cook:
Factorized Computation: What the Neocortex Can Tell Us About the Future of Computing. Frontiers Comput. Neurosci. 12: 54 (2018) - 2017
- [i4]Johannes Thiele, Peter U. Diehl, Matthew Cook:
A wake-sleep algorithm for recurrent, spiking neural networks. CoRR abs/1703.06290 (2017) - 2016
- [j2]Robin Spiess, Richard George, Matthew Cook, Peter U. Diehl:
Structural Plasticity Denoises Responses and Improves Learning Speed. Frontiers Comput. Neurosci. 10: 93 (2016) - [c4]Peter U. Diehl, Guido Zarrella, Andrew Cassidy, Bruno U. Pedroni, Emre Neftci:
Conversion of artificial recurrent neural networks to spiking neural networks for low-power neuromorphic hardware. ICRC 2016: 1-8 - [c3]Peter U. Diehl, Bruno U. Pedroni, Andrew Cassidy, Paul Merolla, Emre Neftci, Guido Zarrella:
TrueHappiness: Neuromorphic emotion recognition on TrueNorth. IJCNN 2016: 4278-4285 - [i3]Peter U. Diehl, Bruno U. Pedroni, Andrew Cassidy, Paul Merolla, Emre Neftci, Guido Zarrella:
TrueHappiness: Neuromorphic Emotion Recognition on TrueNorth. CoRR abs/1601.04183 (2016) - [i2]Peter U. Diehl, Guido Zarrella, Andrew S. Cassidy, Bruno U. Pedroni, Emre Neftci:
Conversion of Artificial Recurrent Neural Networks to Spiking Neural Networks for Low-power Neuromorphic Hardware. CoRR abs/1601.04187 (2016) - [i1]Peter U. Diehl, Matthew Cook:
Learning and Inferring Relations in Cortical Networks. CoRR abs/1608.08267 (2016) - 2015
- [j1]Peter U. Diehl, Matthew Cook:
Unsupervised learning of digit recognition using spike-timing-dependent plasticity. Frontiers Comput. Neurosci. 9: 99 (2015) - [c2]Peter U. Diehl, Daniel Neil, Jonathan Binas
, Matthew Cook, Shih-Chii Liu, Michael Pfeiffer:
Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing. IJCNN 2015: 1-8 - 2014
- [c1]Peter U. Diehl, Matthew Cook:
Efficient implementation of STDP rules on SpiNNaker neuromorphic hardware. IJCNN 2014: 4288-4295
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