Petrovici, Mihai Alexandru

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Deperrois, Nicolas; Petrovici, Mihai A; Senn, Walter; Jordan, Jakob (2024). Learning beyond sensations: how dreams organize neuronal representations. Neuroscience and biobehavioral reviews, 157(105508), p. 105508. Elsevier 10.1016/j.neubiorev.2023.105508


Senden, Mario; van Albada, Sacha J.; Pezzulo, Giovanni; Hashim, Ibrahim; Kroner, Alexander; Kurth, Anno C.; Lanillos, Pablo; Narayanan, Vaishnavi; Pennartz, Cyriel; Petrovici, Mihai A.; Steffen, Lea; Weidler, Tonio; Goebel, Rainer (2023). Modular-integrative modeling: a new framework for building brain models that blend biological realism and functional performance. National Science Review, 11(5) Oxford University Press 10.1093/nsr/nwad318

Petrovici, Mihai Alexandru (23 March 2023). The coming decade of digital brain research - A vision for neuroscience at the intersection of technology and computing 10.5281/zenodo.7764003

Chakrabarty, Samit; Petrovici, Mihai A. (2023). Is neuromorphic computing disruptive enough to 1) advance our understanding of the brain and 2) make the design and working of (bio)electronic devices efficient and scalable? (In Press). Research Directions: Bioelectronics, 1 Cambridge University Press 10.1017/bel.2023.5


Klassert, Robert; Baumbach, Andreas; Petrovici, Mihai A; Gärttner, Martin (2022). Variational learning of quantum ground states on spiking neuromorphic hardware. iScience, 25(8), p. 104707. Elsevier 10.1016/j.isci.2022.104707

Kreutzer, Elena; Senn, Walter; Petrovici, Mihai A (2022). Natural-gradient learning for spiking neurons. eLife, 11 eLife Sciences Publications 10.7554/eLife.66526

Deperrois, Nicolas; Petrovici, Mihai A; Senn, Walter; Jordan, Jakob (2022). Learning cortical representations through perturbed and adversarial dreaming. eLife, 11 eLife Sciences Publications 10.7554/eLife.76384

Kriener, Laura; Göltz, Julian; Petrovici, Mihai A. (28 March 2022). The Yin-Yang dataset. In: NICE 2022: 9th Annual Neuro-Inspired Computational Elements Conference. Neuro-Inspired Computational Elements Conference (pp. 107-111). ACM 10.1145/3517343.3517380

Korcsak-Gorzo, Agnes; Müller, Michael G; Baumbach, Andreas; Leng, Luziwei; Breitwieser, Oliver J; van Albada, Sacha J; Senn, Walter; Meier, Karlheinz; Legenstein, Robert; Petrovici, Mihai A (2022). Cortical oscillations support sampling-based computations in spiking neural networks. PLoS computational biology, 18(3), e1009753. Public Library of Science 10.1371/journal.pcbi.1009753

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

Haider, Paul; Ellenberger, Benjamin; Kriener, Laura; Jordan, Jakob; Senn, Walter; Petrovici, Mihai A. (2021). Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons. Advances in Neural Information Processing Systems (NIPS), 35. MIT Press


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


Kungl, Akos F.; Schmitt, Sebastian; Klähn, Johann; Müller, Paul; Baumbach, Andreas; Dold, Dominik; Kugele, Alexander; Müller, Eric; Koke, Christoph; Kleider, Mitja; Mauch, Christian; Breitwieser, Oliver; Leng, Luziwei; Gürtler, Nico; Güttler, Maurice; Husmann, Dan; Husmann, Kai; Hartel, Andreas; Karasenko, Vitali; Grübl, Andreas; ... (2019). Accelerated Physical Emulation of Bayesian Inference in Spiking Neural Networks. Frontiers in neuroscience, 13(1201), p. 1201. Frontiers Research Foundation 10.3389/fnins.2019.01201

Wunderlich, Timo; Kungl, Akos F.; Müller, Eric; Hartel, Andreas; Stradmann, Yannik; Aamir, Syed Ahmed; Grübl, Andreas; Heimbrecht, Arthur; Schreiber, Korbinian; Stöckel, David; Pehle, Christian; Billaudelle, Sebastian; Kiene, Gerd; Mauch, Christian; Schemmel, Johannes; Meier, Karlheinz; Petrovici, Mihai A. (2019). Demonstrating Advantages of Neuromorphic Computation: A Pilot Study. Frontiers in neuroscience, 13(260) Frontiers Research Foundation 10.3389/fnins.2019.00260

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


Leng, Luziwei; Martel, Roman; Breitwieser, Oliver; Bytschok, Ilja; Senn, Walter; Schemmel, Johannes; Meier, Karlheinz; Petrovici, Mihai Alexandru (2018). Spiking neurons with short-term synaptic plasticity form superior generative networks. Scientific Reports, 8(1), p. 10651. Nature Publishing Group 10.1038/s41598-018-28999-2


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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