We are happy that Tengjun, another lab alumnus graduated with flying colors at this home university in China. Tengjun was a visiting student from Zhejiang University in our group from 2023 to 2024. He workedContinue reading
Tag: neuromorphic
High school students build neuronal circuits
At the annual Tage der Genforschung event, the FMI opens its doors to interested high school students from the neighboring cities. This year team members from our group showed the students how to build simpleContinue reading
New preprint: Improving equilibrium propagation without weight symmetry
I am happy to announce our new preprint on “Improving equilibrium propagation (EP) without weight symmetry through Jacobian homeostasis,” led by Axel. https://arxiv.org/abs/2309.02214 EP prescribes a local learning rule and uses recurrent dynamics for creditContinue reading
A tactile robotic finger tip and a spiking neural network read Braille
This fun project started as a summer student project at Telluride 2021 led and advised by Chiara Bartolozzi and myself. An incredibly motivated group of summer students taught a robotic fingertip with tactile sensors andContinue reading
tinyML Neuromorphic Engineering Forum
Happy to announce the tinyML Neuromorphic Engineering Forum, a virtual one-day meeting on September 27, 2022 to bring the tinyML and neurmorphic community closer. The forum is spearheaded by Charlotte Frenkel and co-organized by colleaguesContinue reading
Spektrum der Wissenschaft story on self-calibration in neuromorphic systems
We are very happy that in their current issue Spektrum der Wissenschaft picked up our collaboration story with Uni Heidelberg on self-calibration through surrogate gradient learning in analog neuromorphic systems.
Quantamagazine covers our work on learning on analog neuromorphic hardware
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
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