Mihai A. Petrovici

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 56

Top Venues

University of Heidelberg, Germany (PHD)

Education History

University of Heidelberg, Germany

PHD

Publications

Julian Göltz, Jimmy Weber, Laura Kriener, Peter Lake, Melika Payvand, Mihai A. Petrovici
DelGrad: Exact gradients in spiking networks for learning transmission delays and weights. CoRR (2024)
Benjamin Ellenberger, Paul Haider, Jakob Jordan, Kevin Max, Ismael Jaras, Laura Kriener, Federico Benitez, Mihai A. Petrovici
Backpropagation through space, time, and the brain. CoRR (2024)
Laura Kriener, Kristin Völk, Ben von Hünerbein, Federico Benitez, Walter Senn, Mihai A. Petrovici
Order from chaos: Interplay of development and learning in recurrent networks of structured neurons. CoRR (2024)
Korbinian Schreiber, Timo Wunderlich, Philipp Spilger, Sebastian Billaudelle, Benjamin Cramer, Yannik Stradmann, Christian Pehle, Eric Müller, Mihai A. Petrovici, Johannes Schemmel, Karlheinz Meier
Emulating insect brains for neuromorphic navigation. CoRR (2024)
Kevin Max, Laura Kriener, Garibaldi Pineda García, Thomas Nowotny, Ismael Jaras, Walter Senn, Mihai A. Petrovici
Learning efficient backprojections across cortical hierarchies in real time. Nat. Mac. Intell. 6 (6) (2024)
Yannik Stradmann, Julian Göltz, Mihai A. Petrovici, Johannes Schemmel, Sebastian Billaudelle
Lu.i - A low-cost electronic neuron for education and outreach. CoRR (2024)
Michele Farisco, Gianluca Baldassarre, Emilio Cartoni, Antonia Leach, Mihai A. Petrovici, Achim Rosemann, Arleen Salles, Bernd Stahl, Sacha J. van Albada
A method for the ethical analysis of brain-inspired AI. Artif. Intell. Rev. 57 (6) (2024)
Nicolas Deperrois, Mihai A. Petrovici, Walter Senn, Jakob Jordan
Learning beyond sensations: how dreams organize neuronal representations. CoRR (2023)
Michele Farisco, Gianluca Baldassarre, Emilio Cartoni, Antonia Leach, Mihai A. Petrovici, Achim Rosemann, Arleen Salles, Bernd Stahl, Sacha J. van Albada
A method for the ethical analysis of brain-inspired AI. CoRR (2023)
Arno Granier, Mihai A. Petrovici, Walter Senn, Katharina A. Wilmes
Precision estimation and second-order prediction errors in cortical circuits. CoRR (2023)
Jason Yik, Soikat Hasan Ahmed, Zergham Ahmed, Brian Anderson, Andreas G. Andreou, Chiara Bartolozzi, Arindam Basu, Douwe den Blanken, Petrut Bogdan, Sander M. Bohté, Younes Bouhadjar, Sonia M. Buckley, Gert Cauwenberghs, Federico Corradi, Guido de Croon, Andreea Danielescu, Anurag Reddy Daram, Mike Davies, Yigit Demirag, Jason Eshraghian, Jeremy Forest, Steve B. Furber, Michael Furlong, Aditya Gilra, Giacomo Indiveri, Siddharth Joshi, Vedant Karia, Lyes Khacef, James C. Knight, Laura Kriener, Rajkumar Kubendran, Dhireesha Kudithipudi, Gregor Lenz, Rajit Manohar, Christian Mayr, Konstantinos P. Michmizos, Dylan R. Muir, Emre Neftci, Thomas Nowotny, Fabrizio Ottati, Ayça Özcelikkale, Noah Pacik-Nelson, Priyadarshini Panda, Pao-Sheng Sun, Melika Payvand, Christian Pehle, Mihai A. Petrovici, Christoph Posch, Alpha Renner, Yulia Sandamirskaya, Clemens JS Schaefer, André van Schaik, Johannes Schemmel, Catherine D. Schuman, Jae-sun Seo, Sumit Bam Shrestha, Manolis Sifalakis, Amos Sironi, Kenneth Stewart, Terrence C. Stewart, Philipp Stratmann, Guangzhi Tang, Jonathan Timcheck, Marian Verhelst, Craig M. Vineyard, Bernhard Vogginger, Amirreza Yousefzadeh, Biyan Zhou, Fatima Tuz Zohora, Charlotte Frenkel, Vijay Janapa Reddi
NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking. CoRR (2023)
Julian Göltz, Sebastian Billaudelle, Laura Kriener, Luca Blessing, Christian Pehle, Eric Müller, Johannes Schemmel, Mihai A. Petrovici
Gradient-based methods for spiking physical systems. CoRR (2023)
Kevin Max, Laura Kriener, Garibaldi Pineda García, Thomas Nowotny, Walter Senn, Mihai A. Petrovici
Learning efficient backprojections across cortical hierarchies in real time. CoRR (2022)
Andreas Baumbach, Robert Klassert, Stefanie Czischek, Martin Gärttner, Mihai A. Petrovici
Quantum many-body states: A novel neuromorphic application. NICE (2022)
Camille Gontier, Jakob Jordan, Mihai A. Petrovici
DELAUNAY: a dataset of abstract art for psychophysical and machine learning research. CoRR (2022)
Laura Kriener, Julian Göltz, Mihai A. Petrovici
The Yin-Yang dataset. NICE (2022)
Agnes Korcsak-Gorzo, Michael G. Müller, Andreas Baumbach, Luziwei Leng, Oliver Julien Breitwieser, Sacha J. van Albada, Walter Senn, Karlheinz Meier, Robert Legenstein, Mihai A. Petrovici
Cortical oscillations support sampling-based computations in spiking neural networks. PLoS Comput. Biol. 18 (3) (2022)
Nicolas Deperrois, Mihai A. Petrovici, Walter Senn, Jakob Jordan
Memory semantization through perturbed and adversarial dreaming. CoRR (2021)
Andreas Baumbach, Sebastian Billaudelle, Virginie Sabado, Mihai A. Petrovici
BrainScaleS: Greater Versatility for Neuromorphic Emulation. ERCIM News 2021 (125) (2021)
Henrik D. Mettler, Maximilian Schmidt, Walter Senn, Mihai A. Petrovici, Jakob Jordan
Evolving neuronal plasticity rules using cartesian genetic programming. GECCO Companion (2021)
Julian Göltz, Laura Kriener, Virginie Sabado, Mihai A. Petrovici
Fast and Energy-efficient Deep Neuromorphic Learning. ERCIM News 2021 (125) (2021)
Robert Klassert, Andreas Baumbach, Mihai A. Petrovici, Martin Gärttner
Variational learning of quantum ground states on spiking neuromorphic hardware. CoRR (2021)
Paul Haider, Benjamin Ellenberger, Laura Kriener, Jakob Jordan, Walter Senn, Mihai A. Petrovici
Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons. CoRR (2021)
Henrik D. Mettler, Maximilian Schmidt, Walter Senn, Mihai A. Petrovici, Jakob Jordan
Evolving Neuronal Plasticity Rules using Cartesian Genetic Programming. CoRR (2021)
Laura Kriener, Julian Göltz, Mihai A. Petrovici
The Yin-Yang dataset. CoRR (2021)
Paul Haider, Benjamin Ellenberger, Laura Kriener, Jakob Jordan, Walter Senn, Mihai A. Petrovici
Latent Equilibrium: Arbitrarily fast computation with arbitrarily slow neurons. NeurIPS (2021)
Julian Göltz, Laura Kriener, Andreas Baumbach, Sebastian Billaudelle, Oliver Breitwieser, Benjamin Cramer, Dominik Dold, Ákos F. Kungl, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
Fast and energy-efficient neuromorphic deep learning with first-spike times. Nat. Mach. Intell. 3 (9) (2021)
Henrik D. Mettler, Virginie Sabado, Walter Senn, Mihai A. Petrovici, Jakob Jordan
Uncovering Neuronal Learning Principles through Artificial Evolution. ERCIM News 2021 (125) (2021)
Sebastian Billaudelle, Benjamin Cramer, Mihai A. Petrovici, Korbinian Schreiber, David Kappel, Johannes Schemmel, Karlheinz Meier
Structural plasticity on an accelerated analog neuromorphic hardware system. Neural Networks 133 (2021)
Sebastian Billaudelle, Yannik Stradmann, Korbinian Schreiber, Benjamin Cramer, Andreas Baumbach, Dominik Dold, Julian Göltz, Ákos Ferenc 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
Versatile Emulation of Spiking Neural Networks on an Accelerated Neuromorphic Substrate. ISCAS (2020)
Korbinian Schreiber, Timo C. Wunderlich, Christian Pehle, Mihai A. Petrovici, Johannes Schemmel, Karlheinz Meier
Closed-loop experiments on the BrainScaleS-2 architecture. NICE (2020)
Jakob Jordan, Mihai A. Petrovici, Walter Senn, João Sacramento
Conductance-based dendrites perform reliability-weighted opinion pooling. NICE (2020)
Elena Kreutzer, Walter M. Senn, Mihai A. Petrovici
Natural-gradient learning for spiking neurons. CoRR (2020)
Sebastian Billaudelle, Yannik Stradmann, Korbinian Schreiber, Benjamin Cramer, Andreas Baumbach, Dominik Dold, Julian Göltz, Ákos Ferenc 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
Live Demonstration: Versatile Emulation of Spiking Neural Networks on an Accelerated Neuromorphic Substrate. ISCAS (2020)
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
Spiking neuromorphic chip learns entangled quantum states. CoRR (2020)
Julian Göltz, Andreas Baumbach, Sebastian Billaudelle, Ákos F. Kungl, Oliver Breitwieser, Karlheinz Meier, Johannes Schemmel, Laura Kriener, Mihai A. Petrovici
Fast and deep neuromorphic learning with first-spike coding. NICE (2020)
Elena Kreutzer, Mihai A. Petrovici, Walter Senn
Natural gradient learning for spiking neurons. NICE (2020)
Sebastian Billaudelle, Yannik Stradmann, Korbinian Schreiber, Benjamin Cramer, Andreas Baumbach, Dominik Dold, Julian Göltz, Ákos 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
Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate. CoRR (2019)
Timo C. Wunderlich, Ákos F. Kungl, Eric Müller, Johannes Schemmel, Mihai A. Petrovici
Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spiking Neural Network. CoRR (2019)
Timo Wunderlich, Ákos F. Kungl, Eric Müller, Johannes Schemmel, Mihai A. Petrovici
Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spiking Neural Network. ICANN (1) (2019)
Sebastian Billaudelle, Benjamin Cramer, Mihai A. Petrovici, Korbinian Schreiber, David Kappel, Johannes Schemmel, Karlheinz Meier
Structural plasticity on an accelerated analog neuromorphic hardware system. CoRR (2019)
Dominik Dold, Ilja Bytschok, Ákos F. Kungl, Andreas Baumbach, Oliver Breitwieser, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
Stochasticity from function - Why the Bayesian brain may need no noise. Neural Networks 119 (2019)
Julian Göltz, Andreas Baumbach, Sebastian Billaudelle, Oliver Breitwieser, Dominik Dold, Laura Kriener, Ákos Ferenc Kungl, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
Fast and deep neuromorphic learning with time-to-first-spike coding. CoRR (2019)
Dominik Dold, Ilja Bytschok, Ákos F. Kungl, Andreas Baumbach, Oliver Breitwieser, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
Stochasticity from function - why the Bayesian brain may need no noise. CoRR (2018)
Ákos F. Kungl, Sebastian Schmitt, Johann Klähn, Paul Müller, Andreas Baumbach, Dominik Dold, Alexander Kugele, Nico Gürtler, Luziwei Leng, Eric Müller, Christoph Koke, Mitja Kleider, Christian Mauch, Oliver Breitwieser, Maurice Güttler, Dan Husmann de Oliveira, Kai Husmann, Joscha Ilmberger, Andreas Hartel, Vitali Karasenko, Andreas Grübl, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
Generative models on accelerated neuromorphic hardware. CoRR (2018)
Timo Wunderlich, Ákos F. Kungl, Eric Müller, 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
Demonstrating Advantages of Neuromorphic Computation: A Pilot Study. CoRR (2018)
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 de Oliveira, 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 N. Thanasoulis, Bernhard Vogginger, Robert Legenstein, Wolfgang Maass, René Schüffny, Christian Mayr, Johannes Schemmel, Karlheinz Meier
Pattern representation and recognition with accelerated analog neuromorphic systems. CoRR (2017)
Mihai A. Petrovici, Sebastian Schmitt, Johann Klähn, Robert D. St. Louis, Anna Schroeder, Guillaume Bellec, Johannes Bill, Oliver Breitwieser, Ilja Bytschok, Andreas Grübl, Maurice Güttler, Andreas Hartel, Stephan Hartmann, Dan Husmann de Oliveira, Kai Husmann, Sebastian Jeltsch, Vitali Karasenko, Mitja Kleider, Christoph Koke, Alexander Kononov, Christian Mauch, Eric Müller, Paul Müller, Johannes Partzsch, Thomas Pfeil, Stefan Schiefer, Stefan Scholze, Anand Subramoney, Vasilis N. Thanasoulis, Bernhard Vogginger, Robert Legenstein, Wolfgang Maass, René Schüffny, Christian Mayr, Johannes Schemmel, Karlheinz Meier
Pattern representation and recognition with accelerated analog neuromorphic systems. ISCAS (2017)
Luziwei Leng, Roman Martel, Oliver Breitwieser, Ilja Bytschok, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
Spiking neurons with short-term synaptic plasticity form superior generative networks. CoRR (2017)
Mihai A. Petrovici, Anna Schroeder, Oliver Breitwieser, Andreas Grübl, Johannes Schemmel, Karlheinz Meier
Robustness from structure: Inference with hierarchical spiking networks on analog neuromorphic hardware. IJCNN (2017)
Sebastian Schmitt, Johann Klähn, Guillaume Bellec, Andreas Grübl, Maurice Güttler, Andreas Hartel, Stephan Hartmann, Dan Husmann de Oliveira, Kai Husmann, Sebastian Jeltsch, Vitali Karasenko, Mitja Kleider, Christoph Koke, Alexander Kononov, Christian Mauch, Eric Müller, Paul Müller, Johannes Partzsch, Mihai A. Petrovici, Stefan Schiefer, Stefan Scholze, Vasilis N. Thanasoulis, Bernhard Vogginger, Robert Legenstein, Wolfgang Maass, Christian Mayr, René Schüffny, Johannes Schemmel, Karlheinz Meier
Neuromorphic hardware in the loop: Training a deep spiking network on the BrainScaleS wafer-scale system. IJCNN (2017)
Mihai A. Petrovici, Anna Schroeder, Oliver Breitwieser, Andreas Grübl, Johannes Schemmel, Karlheinz Meier
Robustness from structure: Inference with hierarchical spiking networks on analog neuromorphic hardware. CoRR (2017)
Sebastian Schmitt, Johann Klaehn, Guillaume Bellec, Andreas Grübl, Maurice Guettler, Andreas Hartel, Stephan Hartmann, Dan Husmann de Oliveira, Kai Husmann, Vitali Karasenko, Mitja Kleider, Christoph Koke, Christian Mauch, Eric Müller, Paul Müller, Johannes Partzsch, Mihai A. Petrovici, Stefan Schiefer, Stefan Scholze, Bernhard Vogginger, Robert Legenstein, Wolfgang Maass, Christian Mayr, Johannes Schemmel, Karlheinz Meier
Neuromorphic Hardware In The Loop: Training a Deep Spiking Network on the BrainScaleS Wafer-Scale System. CoRR (2017)
Mihai A. Petrovici, Johannes Bill, Ilja Bytschok, Johannes Schemmel, Karlheinz Meier
Stochastic inference with spiking neurons in the high-conductance state. CoRR (2016)
Mihai A. Petrovici, Ilja Bytschok, Johannes Bill, Johannes Schemmel, Karlheinz Meier
The high-conductance state enables neural sampling in networks of LIF neurons. CoRR (2016)
Dimitri Probst, Mihai A. Petrovici, Ilja Bytschok, Johannes Bill, Dejan Pecevski, Johannes Schemmel, Karlheinz Meier
Probabilistic inference in discrete spaces can be implemented into networks of LIF neurons. Frontiers Comput. Neurosci. 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
Bridging the gap between software simulation and emulation on neuromorphic hardware: An investigation of causes, effects and compensation of network-level anomalies in a mixed-signal waferscale neuromorphic modeling platform. CoRR (2014)
Mihai A. Petrovici, Johannes Bill, Ilja Bytschok, Johannes Schemmel, Karlheinz Meier
Stochastic inference with deterministic spiking neurons. CoRR (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 Mueller, Johannes Partzsch, Stefan Scholze, Lukas Zühl, Christian Mayr, Alain Destexhe, Markus Diesmann, Tobias C. Potjans, Anders Lansner, René Schüffny, Johannes Schemmel, Karlheinz Meier
A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems. Biol. Cybern. 104 (4-5) (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Mihai A. Petrovici