Author: fzenke online

My lab’s website is online! Moreover, I am looking for PhD students. If you are interested apply for the May 1st 2019 deadline.

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Tutorial on surrogate gradient learning in spiking networks online

Please try this at home! I just put up a beta version of a tutorial showing how to train spiking neural networks with surrogate gradients using PyTorch: Emre, Hesham, and myself are planning to release a more comprehensive collection

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Auryn 0.8.2 released

I am happy to announce a long overdue maintenance release of Auryn v0.8.2m with plenty of fixes and improvements. Most notable improvement are the added support for non x86 architectures such as Arm and PowerPC. Special thanks to Ankur Sinha

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Cosyne 2019 — Talks & poster resources

I am eagerly anticipating fun discussions at Cosyne 2019. We have a poster at the main meeting and I will give two talks at the workshops. If biological learning and spiking neural networks tickle your fancy, come along. I will

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Computational neuroscience at the FMI (now hiring)

I am very excited to start my research group at the FMI in Basel, Switzerland in June 2019. My group will conduct research on learning and memory at the intersection of computational neuroscience and machine learning. The lab will be

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Bernstein Satellite Workshop on “Emergent function in non-random neural networks”

Mark the dates September 25th-26th for our Bernstein Satellite Workshop on “Networks which do stuff” which Guillaume Hennequin, Tim Vogels and myself are organizing this year at the Bernstein meeting in Berlin. Abstract Computation in the brain occurs through complex

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Talk at MPI Göttingen on June 28th

Thrilled to share the latest results on learning in multi-layer spiking networks using biologically plausible surrogate gradients at the “Third workshop on advanced methods in theoretical neuroscience” at the Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany. Thanks to

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SuperSpike: Supervised learning in spiking neural networks — paper and code published

I am happy to announce that the SuperSpike paper and code are finally published. Here is an example of a network with one hidden layer which is learning to produce a Radcliffe Camera spike train from frozen Poisson input spike

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Talk at TU Berlin on Network and Plasticity Dynamics

I am delighted to get the chance to present my work on learning in spiking neural networks on Tuesday, 15th of May 2018 at 10:15am at TU Berlin. Title: What can we learn about synaptic plasticity from spiking neural network

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Neuroplasticity meeting “From Bench to Machine Learning” in July in Guildford, UK

Mark the date for the Neuroplasticity meeting “From Bench to Machine Learning” at the University of Surrey, UK (13 July 2018 – 14 July 2018). This meeting has some really cool speakers which I am eager to meet. I

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