Ákos F. Kungl

According to our database, Ákos F. Kungl authored at least 10 papers between 2018 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Fast and energy-efficient neuromorphic deep learning with first-spike times.

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

Nat. Mach. Intell., 2021

2020

Robust learning algorithms for spiking and rate-based neural networks.

Ákos Ferenc Kungl

PhD thesis, 2020

Fast and deep neuromorphic learning with first-spike coding.

Julian Göltz, Andreas Baumbach, Sebastian Billaudelle, Ákos F. Kungl, Oliver Breitwieser, Karlheinz Meier, Johannes Schemmel, Laura Kriener, Mihai A. Petrovici

Proceedings of the NICE '20: Neuro-inspired Computational Elements Workshop, 2020

Live Demonstration: 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, 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

Proceedings of the IEEE International Symposium on Circuits and Systems, 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, 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

Proceedings of the IEEE International Symposium on Circuits and Systems, 2020

2019

Stochasticity from function - Why the Bayesian brain may need no noise.

Dominik Dold, Ilja Bytschok, Ákos F. Kungl, Andreas Baumbach, Oliver Breitwieser, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici

Neural Networks, 2019

Fast and deep neuromorphic learning with time-to-first-spike coding.

Julian Göltz, Andreas Baumbach, Sebastian Billaudelle, Oliver Breitwieser, Dominik Dold, Laura Kriener, Ákos Ferenc Kungl, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici

CoRR, 2019

Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spiking Neural Network.

Timo Wunderlich, Ákos F. Kungl, Eric Müller, Johannes Schemmel, Mihai A. Petrovici

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Theoretical Neural Computation, 2019

2018

Demonstrating Advantages of Neuromorphic Computation: A Pilot Study.

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

CoRR, 2018

Generative models on accelerated neuromorphic hardware.

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

CoRR, 2018