0000-0003-2632-0427

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Czischek, Stefanie; Baumbach, Andreas; Billaudelle, Sebastian; Cramer, Benjamin; Kades, Lukas; Pawlowski, Jan M.; Oberthaler, Markus; Schemmel, Johannes; Petrovici, Mihai A.; Gasenzer, Thomas; Gärttner, Martin (2022). Spiking neuromorphic chip learns entangled quantum states. SciPost Physics, 12(1) SciPost Foundation 10.21468/SciPostPhys.12.1.039

Billaudelle, Sebastian; Cramer, Benjamin; Petrovici, Mihai A.; Schreiber, Korbinian; Kappel, David; Schemmel, Johannes; Meier, Karlheinz (2021). Structural plasticity on an accelerated analog neuromorphic hardware system. Neural networks, 133, pp. 11-20. Elsevier 10.1016/j.neunet.2020.09.024

Zhao, Chang; Widmer, Yves F.; Diegelmann, Sören; Petrovici, Mihai Alexandru; Sprecher, Simon G.; Senn, Walter (2021). Predictive olfactory learning in Drosophila. Scientific Reports, 11(1), p. 6795. Nature Publishing Group 10.1038/s41598-021-85841-y

Zenke, Friedemann; Bohté, Sander M.; Clopath, Claudia; Comşa, Iulia M.; Göltz, Julian; Maass, Wolfgang; Masquelier, Timothée; Naud, Richard; Neftci, Emre O.; Petrovici, Mihai A.; Scherr, Franz; Goodman, Dan F.M. (2021). Visualizing a joint future of neuroscience and neuromorphic engineering. Neuron, 109(4), pp. 571-575. Cell Press 10.1016/j.neuron.2021.01.009

Göltz, J.; Kriener, L.; Baumbach, A.; Billaudelle, S.; Breitwieser, O.; Cramer, B.; Dold, D.; Kungl, A. F.; Senn, W.; Schemmel, J.; Meier, K.; Petrovici, M. A. (2021). Fast and energy-efficient neuromorphic deep learning with first-spike times. Nature machine intelligence, 3(9), pp. 823-835. Springer Nature 10.1038/s42256-021-00388-x

Jordan, Jakob; Schmidt, Maximilian; Senn, Walter; Petrovici, Mihai A (2021). Evolving interpretable plasticity for spiking networks. eLife, 10 eLife Sciences Publications 10.7554/eLife.66273

Billaudelle, S.; Stradmann, Y.; Schreiber, K.; Cramer, B.; Baumbach, A.; Dold, D.; Goltz, J.; Kungl, A.F.; Wunderlich, T. C.; Hartel, A.; Muller, E.; Breitwieser, O.; Mauch, C.; Kleider, M.; Grubl, A.; Stockel, D.; Pehle, C.; Heimbrecht, A.; Spilger, P.; Kiene, G.; ... (2020). Versatile Emulation of Spiking Neural Networks on an Accelerated Neuromorphic Substrate. IEEE Xplore, pp. 1-5. IEEE 10.1109/ISCAS45731.2020.9180741

Jordan, Jakob; Petrovici, Mihai A.; Breitwieser, Oliver; Schemmel, Johannes; Meier, Karlheinz; Diesmann, Markus; Tetzlaff, Tom (2019). Deterministic networks for probabilistic computing. Scientific reports, 9(1), p. 18303. Springer Nature 10.1038/s41598-019-54137-7

Dold, Dominik; Bytschok, Ilja; Kungl, Akos F.; Baumbach, Andreas; Breitwieser, Oliver; Senn, Walter; Schemmel, Johannes; Meier, Karlheinz; Petrovici, Mihai A. (2019). Stochasticity from function — Why the Bayesian brain may need no noise. Neural networks, 119, pp. 200-213. Elsevier 10.1016/j.neunet.2019.08.002

Petrovici, Mihai Alexandru; Schroeder, Anna; Breitwieser, Oliver; Grubl, Andreas; Schemmel, Johannes; Meier, Karlheinz (2017). Robustness from structure: Inference with hierarchical spiking networks on analog neuromorphic hardware. In: 2017 International Joint Conference on Neural Networks (IJCNN) (pp. 2209-2216). IEEE 10.1109/IJCNN.2017.7966123

Schmitt, Sebastian; Klahn, Johann; Bellec, Guillaume; Grubl, Andreas; Guttler, Maurice; Hartel, Andreas; Hartmann, Stephan; Husmann, Dan; Husmann, Kai; Jeltsch, Sebastian; Karasenko, Vitali; Kleider, Mitja; Koke, Christoph; Kononov, Alexander; Mauch, Christian; Muller, Eric; Muller, Paul; Partzsch, Johannes; Petrovici, Mihai Alexandru; Schiefer, Stefan; ... (2017). Neuromorphic hardware in the loop: Training a deep spiking network on the BrainScaleS wafer-scale system. In: 2017 International Joint Conference on Neural Networks (IJCNN) (pp. 2227-2234). IEEE 10.1109/IJCNN.2017.7966125

Petrovici, Mihai Alexandru; Schmitt, S.; Klahn, J.; Stockel, D.; Schroeder, A.; Bellec, G.; Bill, J.; Breitwieser, O.; Bytschok, I.; Grubl, A.; Guttler, M.; Hartel, A.; Hartmann, S.; Husmann, D.; Husmann, K.; Jeltsch, S.; Karasenko, V.; Kleider, M.; Koke, C.; Kononov, A.; ... (2017). Pattern representation and recognition with accelerated analog neuromorphic systems. In: 2017 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1-4). IEEE 10.1109/ISCAS.2017.8050530

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