Allison Whitten wrote a nice article for Quantamagazine about our recent collaboration with Heidelberg on the BrainScaleS-2 neuromorphic chip. Analog hardware faces similar obstacles as the brain when learning: Neuronal heterogeneity means that you won’tContinue reading
Tag: neuromorphic
Paper: Brain-Inspired Learning on Neuromorphic Substrates
I’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
Hiring: Information processing in spiking neural networks
We are looking for Ph.D. students to work on the computational principles of information processing in spiking neural networks. The project strives to understand computation in the sparse spiking and sparse connectivity regime, in whichContinue reading
Paper: Surrogate gradients for analog neuromorphic computing
Update (22.01.2022): Now published as Cramer, B., Billaudelle, S., Kanya, S., Leibfried, A., Grübl, A., Karasenko, V., Pehle, C., Schreiber, K., Stradmann, Y., Weis, J., et al. (2022). Surrogate gradients for analog neuromorphic computing. PNASContinue reading