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Müller, Eric; Arnold, Elias; Breitwieser, Oliver; Czierlinski, Milena; Emmel, Arne; Kaiser, Jakob; Mauch, Christian; Schmitt, Sebastian; Spilger, Philipp; Stock, Raphael; Stradmann, Yannik; Weis, Johannes; Baumbach, Andreas; Billaudelle, Sebastian; Cramer, Benjamin; Ebert, Falk; Göltz, Julian; Ilmberger, Joscha; Karasenko, Vitali; Kleider, Mitja; ... (2022). A Scalable Approach to Modeling on Accelerated Neuromorphic Hardware. Frontiers in neuroscience, 16, p. 884128. Frontiers Research Foundation 10.3389/fnins.2022.884128
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
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
