| 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 | 508 | 2017 |
| Conversion of analog to spiking neural networks using sparse temporal coding B Rueckauer, SC Liu 2018 IEEE international symposium on circuits and systems (ISCAS), 1-5, 2018 | 116 | 2018 |
| Evaluation of event-based algorithms for optical flow with ground-truth from inertial measurement sensor B Rueckauer, T Delbruck Frontiers in neuroscience 10, 176, 2016 | 104 | 2016 |
| 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 | 91 | 2016 |
| Event-driven sensing for efficient perception: Vision and audition algorithms SC Liu, B Rueckauer, E Ceolini, A Huber, T Delbruck IEEE Signal Processing Magazine 36 (6), 29-37, 2019 | 46 | 2019 |
| NxTF: An API and compiler for deep spiking neural networks on Intel Loihi B Rueckauer, C Bybee, R Goettsche, Y Singh, J Mishra, A Wild ACM Journal on Emerging Technologies in Computing Systems (JETC) 18 (3), 1-22, 2022 | 21 | 2022 |
| Closing the accuracy gap in an event-based visual recognition task B Rückauer, N Känzig, SC Liu, T Delbruck, Y Sandamirskaya arXiv preprint arXiv:1906.08859, 2019 | 12 | 2019 |
| Conversion of analog to spiking neural networks using sparse temporal coding, 2018 IEEE Int. Symp. Circuits and Systems (ISCAS) B Rueckauer, SC Liu IEEE, 2018 | 10 | 2018 |
| New features of receptive fields in mouse retina through spike-triggered covariance J Ahn, B Rueckauer, Y Yoo, YS Goo Experimental neurobiology 29 (1), 38, 2020 | 5 | 2020 |
| Reducing latency in a converted spiking video segmentation network Q Cheni, B Rueckauer, L Li, T Delbruck, SC Liu 2021 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2021 | 4 | 2021 |
| Method and apparatus with neural network layer contraction SC Liu, B Rueckauer, T Delbruck US Patent App. 16/739,543, 2020 | 2 | 2020 |
| Linear approximation of deep neural networks for efficient inference on video data B Rueckauer, SC Liu 2019 27th European Signal Processing Conference (EUSIPCO), 1-5, 2019 | 2 | 2019 |
| Neural network apparatus and method B Ruckauer, SC Liu US Patent App. 16/168,024, 2019 | 2 | 2019 |
| Temporal Pattern Coding in Deep Spiking Neural Networks B Rueckauer, SC Liu International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 1 | 2021 |
| Optimization of Neuroprosthetic Vision via End-to-end Deep Reinforcement Learning B Küçükoğlu, B Rueckauer, N Ahmad, JR van Steveninck, U Güçlü, ... bioRxiv, 2022 | | 2022 |
| P4O: Efficient Deep Reinforcement Learning with Predictive Processing Proximal Policy Optimization B Küçükoğlu, W Borkent, B Rueckauer, N Ahmad, U Güçlü, M van Gerven | | 2021 |
| Method of converting neural network and recognition apparatus using the same B Ruckauer, I Lungu, HU Yuhuang, M Pfeiffer US Patent 10,977,550, 2021 | | 2021 |
| Contraction of dynamically masked deep neural networks for efficient video processing B Rueckauer, SC Liu IEEE Transactions on Circuits and Systems for Video Technology 32 (2), 621-633, 2021 | | 2021 |
| Real-time edge neuromorphic tasting from chemical microsensor arrays N LeBow, B Rueckauer, P Sun, M Rovira, C Jiménez-Jorquera, SC Liu, ... Frontiers in Neuroscience 15, 2021 | | 2021 |
| LiteEdge: Lightweight Semantic Edge Detection Network H Wang, H Mohamed, Z Wang, B Rueckauer, SC Liu International Conference on Computer Vision (ICCV), 1-10, 2021 | | 2021 |
Shih-Chii LiuGroup Leader, University of Zurich / ETH ZurichVerified email at ini.phys.ethz.ch
