Category: fmi
Preprint: The remarkable robustness of surrogate gradient learning for instilling complex function in spiking neural networks
We just put up a new preprint https://www.biorxiv.org/content/10.1101/2020.06.29.176925v1 in which we take a careful look at what makes surrogate gradients work. Spiking neural networks are notoriously hard to train using gradient-based methods due to theirContinue reading
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 machineContinue reading