Form versus function: theory and models for neuronal substrates
Mihai A. Petrovici
Springer Theses 2016, ISBN 978-3-319-39551-7 (Springer Thesis Award)
Structural plasticity on an accelerated analog neuromorphic hardware system
Sebastian Billaudelle*, Benjamin Cramer*, Mihai A. Petrovici, Korbinian Schreiber, David Kappel, Johannes Schemmel, Karlheinz Meier
Neural Networks 133, 11–20 (2021)
Spiking neuromophic chip learns entangled quantum states
Stefanie Czischek, Andreas Baumbach, Sebastian Billaudelle, Benjamin Cramer, Lukas Kades, Jan M. Pawlowski, Markus K. Oberthaler, Johannes Schemmel, Mihai A. Petrovici, Thomas Gasenzer, Martin Gärttner
arXiv:2008.01039 (2020)
Evolving to learn: discovering interpretable plasticity rules for spiking networks
Jakob Jordan*, Maximilian Schmidt*, Walter Senn, Mihai A. Petrovici
arXiv:2005.14149 (2020)
Predictive olfactory learning in Drosophila
Chang Zhao, Yves F. Widmer, Soeren Diegelmann, Mihai A. Petrovici, Simon G. Sprecher, Walter Senn
bioRxiv: 10.1101/2019.12.29.890533 (2020)
Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate
Sebastian Billaudelle*, Yannik Stradmann*, Korbinian Schreiber*, Benjamin Cramer*, Andreas Baumbach*, Dominik Dold*, Julian Göltz*, Akos F. Kungl*, Timo C. Wunderlich*, Andreas Hartel, Eric Müller, Oliver Breitwieser, Christian Mauch, Mitja Kleider, Andreas Grübl, David Stöckel, Christian Pehle, Arthur Heimbrecht, Philipp Spilger, Gerd Kiene, Vitali Karasenko, Walter Senn, Mihai A. Petrovici*°, Johannes Schemmel°, Karlheinz Meier°
IEEE International Symposium on Circuits and Systems (ISCAS), pp. 1-5 (2020)
Fast and deep neuromorphic learning with time-to-first-spike coding
Julian Göltz, Andreas Baumbach, Sebastian Billaudelle, Oliver Breitwieser, Dominik Dold, Laura Kriener, Akos Ferenc Kungl, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
arXiv:1912.11443 (2019)
Deterministic networks for stochastic computing
Jakob Jordan, Mihai A. Petrovici, Oliver Breitwieser, Johannes Schemmel, Karlheinz Meier, Markus Diesmann, Tom Tetzlaff
Scientific Reports 9, 18303 (2019)
Stochasticity from function - why the Bayesian brain may need no noise
Dominik Dold*, Ilja Bytschok*, Akos F. Kungl, Andreas Baumbach, Oliver Breitwieser, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici*
Neural Networks 119, 200-213 (2019)
Accelerated physical emulation of Bayesian inference in spiking neural networks
Akos F. Kungl, Sebastian Schmitt, Johann Klähn, Paul Müller, Andreas Baumbach, Dominik Dold, Alexander Kugele, Nico Gürtler, Eric Müller, Christoph Koke, Mitja Kleider, Christian Mauch, Oliver Bretwieser, Maurice Güttler, Dan Husmann, Kai Husmann, Joscha Ilmberger, Andreas Hartel, Vitali Karasenko, Andreas Grübl, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
Frontiers in Neuroscience 13, 1201 (2019)
Demonstrating Advantages of Neuromorphic Computation: A Pilot Study
Timo Wunderlich, Akos F. Kungl, Andreas Hartel, Yannik Stradmann, Syed Ahmed Aamir, Andreas Grübl, Arthur Heimbrecht, Korbinian Schreiber, David Stöckel, Christian Pehle, Sebastian Billaudelle, Gerd Kiene, Christian Mauch, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
Frontiers in Neuroscience, 13, 260 (2019)
Spiking neurons with short-term synaptic plasticity form superior generative networks
Luziwei Leng*, Roman Martel, Oliver Breitwieser, Ilja Bytschok, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici*
Scientific Reports 8, 10651 (2018)
Pattern representation and recognition with accelerated analog neuromorphic systems
Mihai A. Petrovici*, Sebastian Schmitt*, Johann Klähn*, David Stöckel*, Anna Schroeder*, Guillaume Bellec, Johannes Bill, Oliver Breitwieser, Ilja Bytschok, Andreas Grübl, Maurice Güttler, Andreas Hartel, Stephan Hartmann, Dan Husmann, Kai Husmann, Sebastian Jeltsch, Vitali Karasenko, Mitja Kleider, Christoph Koke, Alexander Kononov, Christian Mauch, Paul Müller, Johannes Partzsch, Thomas Pfeil, Stefan Schiefer, Stefan Scholze, Anand Subramoney, Vasilis Thanasoulis, Bernhard Vogginger, Robert Legenstein, Wolfgang Maass, René Schüffny, Christian Mayr, Johannes Schemmel, Karlheinz Meier
IEEE International Symposium on Circuits and Systems (ISCAS), pp. 1-4 (2017)
Mihai A. Petrovici*, Anna Schroeder*, Oliver Breitwieser, Andreas Grübl, Johannes Schemmel, Karlheinz Meier
International Joint Conference on Neural Networks (IJCNN), pp. 2209-2216 (2017)
Sebastian Schmitt*, Johann Klaehn*, Guillaume Bellec, Andreas Gruebl, Maurice Guettler, Andreas Hartel, Stephan Hartmann, Dan Husmann, Kai Husmann, Vitali Karasenko, Mitja Kleider, Christoph Koke, Christian Mauch, Eric Mueller, Paul Mueller, Johannes Partzsch, Mihai A. Petrovici, Stefan Schiefer, Stefan Scholze, Bernhard Vogginger, Robert Legenstein, Wolfgang Maass, Christian Mayr, Johannes Schemmel, Karlheinz Meier
2017 International Joint Conference on Neural Networks (IJCNN), pp. 2227-2234 (2017)
Stochastic inference with spiking neurons in the high-conductance state
Mihai A. Petrovici*, Johannes Bill*, Ilja Bytschok, Johannes Schemmel, Karlheinz Meier
Physical Review E 94, 042312 (2016)
Probabilistic inference in discrete spaces can be implemented into networks of LIF neurons
Dimitri Probst*, Mihai A. Petrovici*, Ilja Bytschok, Johannes Bill, Dejan Pecevski, Johannes Schemmel, Karlheinz Meier
Frontiers in Computational Neurocience 9 (2015)
Mihai A. Petrovici, Bernhard Vogginger, Paul Müller, Oliver Breitwieser, Mikael Lundqvist, Lyle Muller, Matthias Ehrlich, Alain Destexhe, Anders Lansner, René Schüffny, Johannes Schemmel, Karlheinz Meier
PLOS ONE e108590 (2014)
Stochastic inference with deterministic spiking neurons
Mihai A. Petrovici*, Johannes Bill*, Ilja Bytschok, Johannes Schemmel, Karlheinz Meier
arXiv 1311.3211 (2013)
Six networks on a universal neuromorphic computing substrate
Thomas Pfeil*, Andreas Grübl*, Sebastian Jeltsch*, Eric Müller*, Paul Müller*, Mihai A. Petrovici*, Michael Schmuker*, Daniel Brüderle, Johannes Schemmel, Karlheinz Meier
Frontiers in Neuroscience 7 (2013)
Daniel Brüderle, Mihai A. Petrovici, Bernhard Vogginger, Matthias Ehrlich, Thomas Pfeil, Sebastian Millner, Andreas Grübl, Karsten Wendt, Eric Müller, Marc-Olivier Schwartz, Dan Husmann de Oliveira, Sebastian Jeltsch, Johannes Fieres, Moritz Schilling, Paul Müller, Oliver Breitwieser, Venelin Petkov, Lyle Muller, Andrew P. Davison, Pradeep Krishnamurthy, Jens Kremkow, Mikael Lundqvist, Eilif Muller, Johannes Partzsch, Stefan Scholze, Lukas Zühl, Christian Mayr, Alain Destexhe, Markus Diesmann, Tobias C. Potjans, Anders Lansner, René Schüffny, Johannes Schemmel, Karlheinz Meier
Biological Cybernetics 104, no. 4-5, 263-296 (2011)
ALICE: Physics Performance Report
The ALICE Collaboration
Journal of Physics G: Nuclear and Particle Physics 30 (11), 1517 (2004)
Deep reinforcement learning for time-continuous substrates
Akos F. Kungl*, Dominik Dold*, Oskar Riedler, Mihai A. Petrovici, Walter Senn
Neuro-Inspired Computational Elements Workshop (NICE) 2020
Natural gradient learning for spiking neurons
E. Kreutzer, M. A. Petrovici°, W. Senn°
Computational and Systems Neuroscience (Cosyne) 2020, Neuro-Inspired Computational Elements Workshop (NICE) 2020
Fast and deep neuromorphic learning with first-spike coding
J. Göltz, A. Baumbach, S. Billaudelle, O. Breitwieser, L. Kriener, A. F. Kungl, K. Meier, J. Schemmel, M. A. Petrovici
Computational and Systems Neuroscience (Cosyne) 2020, Neuro-Inspired Computational Elements Workshop (NICE) 2020, From Neuroscience to Artificially Intelligent Systems (NAISys) 2020
Conductance-based dendrites perform reliability-weighted opinion pooling
Jakob Jordan, Mihai A. Petrovici, Walter Senn, João Sacramento
Computational and Systems Neuroscience (Cosyne) 2020, Neuro-Inspired Computational Elements Workshop (NICE) 2020, From Neuroscience to Artificially Intelligent Systems (NAISys) 2020
Closed-loop experiments on the BrainScaleS-2 architecture
K. Schreiber, T. C. Wunderlich, C. Pehle, M. A. Petrovici°, J. Schemmel°, K. Meier°
Neuro-Inspired Computational Elements Workshop (NICE) 2020
Structural plasticity on spiking neuromorphic hardware
Sebastian Billaudelle, Benjamin Cramer, Mihai A. Petrovici, Johannes Schemmel
Neuro-Inspired Computational Elements Workshop (NICE) 2020
An energy-based model of folded autoencoders for unsupervised learning in cortical hierarchies
Dominik Dold, João Sacramento, Akos F. Kungl, Walter Senn and Mihai A. Petrovici
Bernstein Conference - Berlin, 2019
Deep reinforcement learning in a time-continuous model
Akos F. Kungl, Dominik Dold, Oskar Riedler, Mihai A. Petrovici, Walter Senn
Bernstein Conference - Berlin, 2019
Magnetic phenomena in ensembles of spiking neurons
Andreas Baumbach, Johannes Schemmel, Mihai A. Petrovici
Bernstein Conference - Berlin, 2019
Biological solutions to the mixing problem
Luziwei Leng, Agnes Korcsák-Gorzó, Oliver Breitwieser, Roman Martel, Ilja Bytschok, Walter Senn, Johannes Bill, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
IRCN 2019, best poster award
Timo Wunderlich, Akos F. Kungl, Eric Müller, Johannes Schemmel, Mihai A. Petrovici
ICANN - Theoretical neural computation / Lecture Notes on Computer Science 11727, 119-122 (2019)
Lagrangian dynamics of dendritic microcircuits enables real-time backpropagation of errors
Dominik Dold, Akos F. Kungl, João Sacramento, Mihai A. Petrovici, Kaspar Schindler, Jonathan Binas, Yoshua Bengio, Walter Senn
Selected talk at Cosyne (2019)
Jakob Jordan, João Sacramento, Mihai A Petrovici, Walter Senn
Cosyne abstracts (2019)
Magnetic Phenomena in Spiking Neural Networks
A. Baumbach, A. F. Kungl, M. A. Petrovici, J. Schemmel, K. Meier
Fruehjahrstagung der DPG (2018)
Bayesian computing with spikes
A. Baumbach, M. A. Petrovici, L. Leng, O. J. Breitwieser, D. Stoeckel, I. Bytschok, J. Schemmel, K. Meier
1st HBP Student Conference (2017)
Simulated Tempering in Biologically Inspired Neural Networks
Agnes Korcsak-Gorzo, Luziwei Leng, Oliver Julien Breitwieser, Johannes Schemmel, Karlheinz Meier, Mihai Alexandru Petrovici
Deutsche Physikerinnentagung (2017)
Stochastic computation on spiking neuromorphic hardware
Dominik Dold, Ákos F. Kungl, Andreas Baumbach, Johann Klähn, Ilja Bytschok, Paul Müller, Oliver Breitwieser, Andreas Grübl, Maurice Güttler, Dan Husmann, Mitja Kleider, Christoph Koke, Alexander Kugele, Christian Mauch, Eric Müller, Sebastian Schmitt, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
Bernstein Conference (2017)
Spike-based probabilistic inference with correlated noise
Ilja Bytschok*, Dominik Dold*, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici*
CNS / BMC Neuroscience 18 (Suppl 1):P200 (2017)
Stochastic inference with spiking neural networks
Mihai A. Petrovici*, Luziwei Leng*, Oliver Breitwieser*, David Stöckel*, Ilja Bytschok, Roman Martel, Johannes Bill, Johannes Schemmel, Karlheinz Meier
CNS / BMC Neuroscience 17(Suppl 1):P96 (2016)
Spiking neural networks as superior generative and discriminative models
Luziwei Leng*, Mihai A. Petrovici*, Roman Martel, Ilja Bytschok, Oliver Breitwieser, Johannes Bill, Johannes Schemmel, Karlheinz Meier
Cosyne Abstracts (2016)
Fast sampling with neuromorphic hardware
Mihai A. Petrovici*, David Stöckel*, Ilja Bytschok, Johannes Bill, Thomas Pfeil, Johannes Schemmel, Karlheinz Meier
Demonstration, Advances in Neural Information Processing Systems (NIPS) 28, (2015)
The high-conductance state enables neural sampling in networks of LIF neurons
Mihai A. Petrovici, Ilja Bytschok, Johannes Bill, Johannes Schemmel and Karlheinz Meier
CNS / BMC Neuroscience 16(Suppl 1):O2, selected for oral presentation (2015)
Deterministic neural networks as sources of uncorrelated noise for probabilistic computations
Jakob Jordan, Tom Tetzlaff, Mihai Petrovici, Oliver Breitwieser, Ilja Bytschok, Johannes Bill, Johannes Schemmel, Karlheinz Meier and Markus Diesmann
CNS / BMC Neuroscience 16(Suppl 1):P62 (2015)
