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Peter Udo Diehl
Titre
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Année
Unsupervised Learning of Digit Recognition Using Spike-Timing-Dependent Plasticity
PU Diehl, M Cook
Frontiers in Computational Neuroscience, 2015
11352015
Fast-Classifying, High-Accuracy Spiking Deep Networks Through Weight and Threshold Balancing
PU Diehl, D Neil, J Binas, M Cook, SC Liu, M Pfeiffer
IEEE International Joint Conference on Neural Networks (IJCNN), 2015
8652015
Conversion of Artificial Recurrent Neural Networks to Spiking Neural Networks for Low
PU Diehl, G Zarrella, A Cassidy, BU Pedroni, E Neftci
IEEE International Conference on Rebooting Computing (ICRC), 2016
2052016
Conversion of Artificial Recurrent Neural Networks to Spiking Neural Networks for Low-power Neuromorphic Hardware
PU Diehl, G Zarrella, A Cassidy, BU Pedroni, E Neftci
IEEE International Conference on Rebooting Computing (ICRC), 2016
2052016
Audiometric Characteristics of Hyperacusis Patients
J Sheldrake, PU Diehl, R Schaette
Frontiers in Neurology 6 (105), 2015
1272015
TrueHappiness: Neuromorphic Emotion Recognition on TrueNorth
PU Diehl, BU Pedroni, A Cassidy, P Merolla, E Neftci, G Zarrella
International Joint Conference on Neural Networks (IJCNN), 2016
812016
Conversion of Artificial Recurrent Neural Networks to Spiking Neural Networks for Low-power Neuromorphic Hardware
PU Diehl, D Neil, J Binas, M Cook, SC Liu, M Pfeiffer
International Joint Conference on Neural Networks (IJCNN), 1-8, 2015
46*2015
Efficient Implementation of STDP Rules on SpiNNaker Neuromorphic Hardware
PU Diehl, M Cook
International Joint Conference on Neural Networks (IJCNN) 2014, 4288 - 4295, 2014
42*2014
Abnormal Auditory Gain in Hyperacusis: Investigation with a Computational Model
PU Diehl, R Schaette
Frontiers in neurology 6, 2015
402015
Structural plasticity denoises responses and improves learning speed
R Spiess, R George, M Cook, PU Diehl
Frontiers in computational neuroscience 10, 93, 2016
262016
Learning and inferring relations in cortical networks
PU Diehl, M Cook
arXiv preprint arXiv:1608.08267, 2016
232016
A wake-sleep algorithm for recurrent, spiking neural networks
J Thiele, P Diehl, M Cook
NIPS 2016 workshop "Computing with Spikes", 2017
152017
Modeling the interplay between Structural Plasticity and Spike-timing-dependent Plasticity
RM George, PU Diehl, M Cook, C Mayr, G Indiveri
Computational Neuroscience Meeting (CNS2015), 2015
52015
Restoring speech intelligibility for hearing aid users with deep learning
PU Diehl, Y Singer, H Zilly, U Schönfeld, P Meyer-Rachner, M Berry, ...
Scientific Reports 13 (1), 2719, 2023
12023
Non-intrusive deep learning-based computational speech metrics with high-accuracy across a wide range of acoustic scenes
PU Diehl, L Thorbergsson, Y Singer, V Skripniuk, A Pudszuhn, ...
Plos one 17 (11), e0278170, 2022
12022
Hearing Device System And Method For Processing Audio Signals
PU Diehl, E Sprengel
US Patent App. 17/608,353, 2022
12022
Signal processing device, system and method for processing audio signals
PU Diehl, E Sprengel
US Patent App. 17/425,248, 2022
12022
Factorized computation: What the Neocortex can tell us about the future of computing
PU Diehl, J Martel, J Buhmann, M Cook
Frontiers in computational neuroscience 12, 54, 2018
12018
Performant spiking systems
PU Diehl
ETH Zurich, 2016
12016
Signal processing device, system and method for processing audio signals
PU Diehl, E Sprengel
US Patent App. 17/425,256, 2022
2022
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