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Thomas Pfeil
Thomas Pfeil
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Year
Deep learning with spiking neurons: Opportunities & challenges
M Pfeiffer, T Pfeil
Frontiers in Neuroscience 12, 774, 2018
8262018
Six networks on a universal neuromorphic computing substrate
T Pfeil, A Grübl, S Jeltsch, E Müller, P Müller, MA Petrovici, M Schmuker, ...
Frontiers in neuroscience 7, 2013
2282013
A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems
D Brüderle, MA Petrovici, B Vogginger, M Ehrlich, T Pfeil, S Millner, ...
Biological cybernetics 104, 263-296, 2011
1492011
Efficient Processing of Spatio-Temporal Data Streams With Spiking Neural Networks
A Kugele, T Pfeil, M Pfeiffer, E Chicca
Frontiers in Neuroscience 14, 2020
1362020
Is a 4-bit synaptic weight resolution enough?–constraints on enabling spike-timing dependent plasticity in neuromorphic hardware
T Pfeil, TC Potjans, S Schrader, W Potjans, J Schemmel, M Diesmann, ...
Frontiers in Neuroscience 6, 2012
1242012
A neuromorphic network for generic multivariate data classification
M Schmuker, T Pfeil, MP Nawrot
Proceedings of the National Academy of Sciences 111 (6), 2081-2086, 2014
1152014
Hybrid SNN-ANN: Energy-efficient classification and object detection for event-based vision
A Kugele, T Pfeil, M Pfeiffer, E Chicca
DAGM German Conference on Pattern Recognition, 297-312, 2021
432021
Effect of Heterogeneity on Decorrelation Mechanisms in Spiking Neural Networks: A Neuromorphic-Hardware Study
T Pfeil, J Jordan, T Tetzlaff, A Grübl, J Schemmel, M Diesmann, K Meier
Physical Review X 6 (2), 021023, 2016
352016
SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning
M Nonnenmacher, T Pfeil, I Steinwart, D Reeb
International Conference on Learning Representations, 2021
302021
Pattern representation and recognition with accelerated analog neuromorphic systems
MA Petrovici, S Schmitt, J Klähn, D Stöckel, A Schroeder, G Bellec, J Bill, ...
2017 IEEE International Symposium on Circuits and Systems (ISCAS), 1-4, 2017
232017
Neuromorphic learning towards nano second precision
T Pfeil, AC Scherzer, J Schemmel, K Meier
The 2013 International Joint Conference on Neural Networks (IJCNN), 1-5, 2013
222013
The streaming rollout of deep networks-towards fully model-parallel execution
V Fischer, J Köhler, T Pfeil
Advances in Neural Information Processing Systems, 4039-4050, 2018
162018
Exploring the potential of brain-inspired computing
T Pfeil
82015
Configuration strategies for neurons and synaptic learning in large-scale neuromorphic hardware systems
T Pfeil
Diploma thesis (English), University of Heidelberg, HD-KIP 11-34, 2011
62011
Fast sampling with neuromorphic hardware
MA Petrovici, D Stöckel, I Bytschok, J Bill, T Pfeil, J Schemmel, K Meier
arXiv preprint arXiv:1311.3211, 2013
42013
How many events make an object? Improving single-frame object detection on the 1 Mpx Dataset
A Kugele, T Pfeil, M Pfeiffer, E Chicca
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
22023
Neural networks as sources of uncorrelated noise for functional neural systems
J Jordan, I Bytschok, T Tetzlaff, T Pfeil, O Breitwieser, J Bill, M Diesmann, ...
OCCAM 2014, 2014
22014
Machine learning system, as well as a method, a computer program, and a device for creating the machine learning system
T Pfeil
US Patent 11,790,218, 2023
12023
Device and method for ascertaining a physical property of a physical object
A Kugele, M Pfeiffer, T Pfeil
US Patent App. 17/379,328, 2022
12022
METHOD, DEVICE, AND COMPUTER PROGRAM FOR OPERATING A DEEP NEURAL NETWORK
T Pfeil, V Fischer
US Patent App. 17/429,105, 2022
12022
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