Oliver Breitwieser
Oliver Breitwieser
Dr. rer. nat., Heidelberg University
Bestätigte E-Mail-Adresse bei
Zitiert von
Zitiert von
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
Fast and energy-efficient neuromorphic deep learning with first-spike times
J Göltz, L Kriener, A Baumbach, S Billaudelle, O Breitwieser, B Cramer, ...
Nature Machine Intelligence 3 (9), 823-835, 2021
Characterization and compensation of network-level anomalies in mixed-signal neuromorphic modeling platforms
MA Petrovici, B Vogginger, P Müller, O Breitwieser, M Lundqvist, L Muller, ...
PloS one 9 (10), e108590, 2014
Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate
S Billaudelle, Y Stradmann, K Schreiber, B Cramer, A Baumbach, D Dold, ...
2020 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2020
Spiking neurons with short-term synaptic plasticity form superior generative networks
L Leng, R Martel, O Breitwieser, I Bytschok, W Senn, J Schemmel, K Meier, ...
Scientific reports 8 (1), 10651, 2018
Nest 2.12. 0
S Kunkel, R Deepu, HE Plesser, B Golosio, ME Lepperød, JM Eppler, ...
Jülich Supercomputing Center, 2017
Fast and deep neuromorphic learning with first-spike coding
J Göltz, A Baumbach, S Billaudelle, AF Kungl, O Breitwieser, K Meier, ...
Proceedings of the 2020 Annual Neuro-Inspired Computational Elements …, 2020
Accelerated physical emulation of Bayesian inference in spiking neural networks
AF Kungl, S Schmitt, J Klähn, P Müller, A Baumbach, D Dold, A Kugele, ...
Frontiers in neuroscience 13, 1201, 2019
Stochasticity from function—why the bayesian brain may need no noise
D Dold, I Bytschok, AF Kungl, A Baumbach, O Breitwieser, W Senn, ...
Neural networks 119, 200-213, 2019
hxtorch: PyTorch for BrainScaleS-2: Perceptrons on Analog Neuromorphic Hardware
P Spilger, E Müller, A Emmel, A Leibfried, C Mauch, C Pehle, J Weis, ...
IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile …, 2020
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
Deterministic networks for probabilistic computing
J Jordan, MA Petrovici, O Breitwieser, J Schemmel, K Meier, M Diesmann, ...
Scientific reports 9 (1), 18303, 2019
25th annual computational neuroscience meeting: CNS-2016
TO Sharpee, A Destexhe, M Kawato, V Sekulić, FK Skinner, DK Wójcik, ...
BMC neuroscience 17, 1-112, 2016
Extending BrainScaleS OS for BrainScaleS-2
E Müller, C Mauch, P Spilger, OJ Breitwieser, J Klähn, D Stöckel, ...
arXiv preprint arXiv:2003.13750, 2020
A scalable approach to modeling on accelerated neuromorphic hardware
E Müller, E Arnold, O Breitwieser, M Czierlinski, A Emmel, J Kaiser, ...
Frontiers in neuroscience 16, 884128, 2022
Inference with artificial neural networks on analog neuromorphic hardware
J Weis, P Spilger, S Billaudelle, Y Stradmann, A Emmel, E Müller, ...
IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile …, 2020
Cortical oscillations support sampling-based computations in spiking neural networks
A Korcsak-Gorzo, MG Müller, A Baumbach, L Leng, OJ Breitwieser, ...
PLoS computational biology 18 (3), e1009753, 2022
Demonstrating analog inference on the brainscales-2 mobile system
Y Stradmann, S Billaudelle, O Breitwieser, FL Ebert, A Emmel, ...
IEEE Open Journal of Circuits and Systems 3, 252-262, 2022
Towards a neuromorphic implementation of spike-based expectation maximization
O Breitwieser
Masterarbeit, Universität Heidelberg, 2015
Fast and deep: energy-efficient neuromorphic learning with first-spike times
J Göltz, L Kriener, A Baumbach, S Billaudelle, O Breitwieser, B Cramer, ...
arXiv preprint arXiv:1912.11443, 2019
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