Mihai A. Petrovici
Mihai A. Petrovici
Department of Physiology, University of Bern / Kirchhoff-Institute for Physics, Heidelberg
Verified email at unibe.ch - Homepage
Cited by
Cited by
ALICE: Physics performance report, volume I
F Carminati, P Foka, P Giubellino, A Morsch, G Paic, JP Revol, K Safarik, ...
Journal of Physics G: Nuclear and Particle Physics 30 (11), 1517, 2004
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, 11, 2013
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
Neuromorphic hardware in the loop: Training a deep spiking network on the brainscales wafer-scale system
S Schmitt, J Klähn, G Bellec, A Grübl, M Guettler, A Hartel, S Hartmann, ...
2017 international joint conference on neural networks (IJCNN), 2227-2234, 2017
Stochastic inference with spiking neurons in the high-conductance state
MA Petrovici, J Bill, I Bytschok, J Schemmel, K Meier
Physical Review E 94 (4), 042312, 2016
Demonstrating advantages of neuromorphic computation: a pilot study
T Wunderlich, AF Kungl, E Müller, A Hartel, Y Stradmann, SA Aamir, ...
Frontiers in neuroscience 13, 260, 2019
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
Form versus function: theory and models for neuronal substrates
MA Petrovici
Springer, 2016
Probabilistic inference in discrete spaces can be implemented into networks of LIF neurons
D Probst, MA Petrovici, I Bytschok, J Bill, D Pecevski, J Schemmel, ...
Frontiers in Computational Neuroscience 9, 13, 2015
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
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
Pattern representation and recognition with accelerated analog neuromorphic systems
MA Petrovici, S Schmitt, J Klähn, D Stöckel, A Schroeder, G Bellec, J Bill, ...
Circuits and Systems (ISCAS), 2017 IEEE International Symposium on, 1-4, 2017
Deterministic networks for probabilistic computing
J Jordan, MA Petrovici, O Breitwieser, J Schemmel, K Meier, M Diesmann, ...
Scientific Reports 9 (1), 1-17, 2019
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
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
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
Robustness from structure: Inference with hierarchical spiking networks on analog neuromorphic hardware
MA Petrovici, A Schroeder, O Breitwieser, A Grübl, J Schemmel, K Meier
Neural Networks (IJCNN), 2017 International Joint Conference on, 2209-2216, 2017
Structural plasticity on an accelerated analog neuromorphic hardware system
S Billaudelle, B Cramer, MA Petrovici, K Schreiber, D Kappel, ...
Neural Networks 133, 11-20, 2021
25th annual computational neuroscience meeting: CNS-2016
TO Sharpee, A Destexhe, M Kawato, V Sekulić, FK Skinner, DK Wójcik, ...
BMC Neuroscience 17 (1), 54, 2016
Evolving to learn: discovering interpretable plasticity rules for spiking networks
J Jordan, M Schmidt, W Senn, MA Petrovici
arXiv preprint arXiv:2005.14149, 2020
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