| Fast-Classifying, High-Accuracy Spiking Deep Networks Through Weight and Threshold Balancing PU Diehl, D Neil, J Binas, M Cook, SC Liu, M Pfeiffer International Joint Conference on Neural Networks (IJCNN), 2015 | 1184 | 2015 |
| Training deep spiking neural networks using backpropagation JH Lee, T Delbruck, M Pfeiffer Frontiers in neuroscience 10, 508, 2016 | 1102 | 2016 |
| Conversion of continuous-valued deep networks to efficient event-driven networks for image classification B Rueckauer, IA Lungu, Y Hu, M Pfeiffer, SC Liu Frontiers in neuroscience 11, 682, 2017 | 1070 | 2017 |
| Gland segmentation in colon histology images: The glas challenge contest K Sirinukunwattana, JPW Pluim, H Chen, X Qi, PA Heng, YB Guo, ... Medical image analysis 35, 489-502, 2017 | 835 | 2017 |
| Deep learning with spiking neurons: opportunities and challenges M Pfeiffer, T Pfeil Frontiers in neuroscience 12, 409662, 2018 | 766 | 2018 |
| Phased LSTM: Accelerating recurrent network training for long or event-based sequences D Neil, M Pfeiffer, SC Liu Advances in Neural Information Processing Systems, 3882-3890, 2016 | 559 | 2016 |
| Real-time classification and sensor fusion with a spiking deep belief network P O'Connor, D Neil, SC Liu, T Delbruck, M Pfeiffer Frontiers in neuroscience 7, 178, 2013 | 532 | 2013 |
| Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity B Nessler, M Pfeiffer, L Büsing, W Maass PLoS Computational Biology 9 (4), e1003037, 2013 | 332 | 2013 |
| DVS benchmark datasets for object tracking, action recognition, and object recognition Y Hu, H Liu, M Pfeiffer, T Delbruck Frontiers in neuroscience 10, 405, 2016 | 159 | 2016 |
| Robust anomaly detection in images using adversarial autoencoders L Beggel, M Pfeiffer, B Bischl Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020 | 158 | 2020 |
| Theory and tools for the conversion of analog to spiking convolutional neural networks B Rueckauer, IA Lungu, Y Hu, M Pfeiffer arXiv preprint arXiv:1612.04052, 2016 | 151 | 2016 |
| STDP enables spiking neurons to detect hidden causes of their inputs B Nessler, M Pfeiffer, W Maass Advances in neural information processing systems 22, 2009 | 149 | 2009 |
| Robustness of spiking deep belief networks to noise and reduced bit precision of neuro-inspired hardware platforms E Stromatias, D Neil, M Pfeiffer, F Galluppi, SB Furber, SC Liu Frontiers in neuroscience 9, 222, 2015 | 140 | 2015 |
| Segmentation and classification of colon glands with deep convolutional neural networks and total variation regularization P Kainz, M Pfeiffer, M Urschler PeerJ 5, e3874, 2017 | 135 | 2017 |
| Deep learning-based object classification on automotive radar spectra K Patel, K Rambach, T Visentin, D Rusev, M Pfeiffer, B Yang 2019 IEEE Radar Conference (RadarConf), 1-6, 2019 | 134 | 2019 |
| Efficient processing of spatio-temporal data streams with spiking neural networks A Kugele, T Pfeil, M Pfeiffer, E Chicca Frontiers in neuroscience 14, 512192, 2020 | 124 | 2020 |
| Scalable Energy-Efficient, Low-Latency Implementations of Spiking Deep Belief Networks on SpiNNaker E Stromatias, D Neil, M Pfeiffer, F Galluppi, S Furber, SC Liu IEEE International Joint Conference on Neural Networks (IJCNN), 2015 | 107* | 2015 |
| Learning to be efficient: Algorithms for training low-latency, low-compute deep spiking neural networks D Neil, M Pfeiffer, SC Liu Proceedings of the 31st annual ACM symposium on applied computing, 293-298, 2016 | 93 | 2016 |
| Real-time gesture interface based on event-driven processing from stereo silicon retinas JH Lee, T Delbruck, M Pfeiffer, PKJ Park, CW Shin, H Ryu, BC Kang IEEE transactions on neural networks and learning systems 25 (12), 2250-2263, 2014 | 84 | 2014 |
| A framework for plasticity implementation on the SpiNNaker neural architecture F Galluppi, X Lagorce, E Stromatias, M Pfeiffer, LA Plana, SB Furber, ... Frontiers in neuroscience 8, 429, 2015 | 67 | 2015 |
Shih-Chii LiuInstitute of Neuroinformatics, University of Zurich & ETH ZurichVerified email at ini.phys.ethz.ch
