Search Results for author: Julian Göltz

Found 5 papers, 2 papers with code

Gradient-based methods for spiking physical systems

no code implementations29 Aug 2023 Julian Göltz, Sebastian Billaudelle, Laura Kriener, Luca Blessing, Christian Pehle, Eric Müller, Johannes Schemmel, Mihai A. Petrovici

Recent efforts have fostered significant progress towards deep learning in spiking networks, both theoretical and in silico.

The Yin-Yang dataset

1 code implementation16 Feb 2021 Laura Kriener, Julian Göltz, Mihai A. Petrovici

The Yin-Yang dataset was developed for research on biologically plausible error backpropagation and deep learning in spiking neural networks.

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