Computational neuroscientist at the FMI in Basel (zenkelab.org). Main interests: Learning, memory, and information processing in biologically inspired (spiking) neural networks.
- Publication: Visualizing a joint future of neuroscience and neuromorphic engineeringHappy to share this report summarizing the key contributions, discussion outcomes, and future research directions as presented at the spiking neural networks as universal function approximators meeting SNUFA2020. Paper: https://www.cell.com/neuron/fulltext/S0896-6273(21)00009-XAuthor link: https://authors.elsevier.com/a/1cbg3_KOmxI%7E6f Read more »
- Paper: Brain-Inspired Learning on Neuromorphic SubstratesI’m happy to share our new overview paper (https://ieeexplore.ieee.org/document/9317744, preprint: arxiv.org/abs/2010.11931) on brain-inspired learning on neuromorphic substrates in (spiking) recurrent neural networks. We systematically analyze how the combination of Real-Time-Recurrent Learning (RTRL; Williams and Zipser,Continue reading Read more »
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