| Deep learning with spiking neurons: Opportunities & challenges M Pfeiffer, T Pfeil Frontiers in Neuroscience 12, 774, 2018 | 1032 | 2018 |
| 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 | 248 | 2013 |
| Efficient Processing of Spatio-Temporal Data Streams With Spiking Neural Networks A Kugele, T Pfeil, M Pfeiffer, E Chicca Frontiers in Neuroscience 14, 2020 | 163 | 2020 |
| 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 (4), 263-296, 2011 | 152 | 2011 |
| 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 | 135 | 2012 |
| 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 | 125 | 2014 |
| 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 | 65 | 2021 |
| SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning M Nonnenmacher, T Pfeil, I Steinwart, D Reeb International Conference on Learning Representations, 2021 | 60 | 2021 |
| 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 | 38 | 2016 |
| 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 | 23 | 2017 |
| 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 | 23 | 2013 |
| 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 | 18 | 2018 |
| Exploring the potential of brain-inspired computing T Pfeil | 8 | 2015 |
| 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 | 6 | 2011 |
| 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 | 4 | 2023 |
| 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 | 4 | 2013 |
| 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 | 3 | 2014 |
| 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 | 2 | 2023 |
| METHOD, DEVICE, AND COMPUTER PROGRAM FOR OPERATING A DEEP NEURAL NETWORK T Pfeil, V Fischer US Patent App. 17/429,105, 2022 | 2 | 2022 |
| Device and method for ascertaining a physical property of a physical object A Kugele, M Pfeiffer, T Pfeil US Patent 12,430,922, 2025 | 1 | 2025 |
Michael PfeifferBosch Center for Artificial IntelligenceVerified email at de.bosch.com
