Bodo Rueckauer
Bodo Rueckauer
PhD candidate, Institute of Neuroinformatics, ETH Zurich and University of Zurich
Verified email at
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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
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
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
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
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
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
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
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
Neural network apparatus and method
B Ruckauer, SC Liu
US Patent App. 16/168,024, 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
arXiv preprint arXiv:2101.04261, 2021
Method and apparatus with neural network layer contraction
S Liu, B Rueckauer, T Delbruck
US Patent App. 16/739,543, 2020
Method of converting neural network and recognition apparatus using the same
B Ruckauer, I Lungu, HU Yuhuang, M Pfeiffer
US Patent App. 15/631,058, 2018
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