18 citations · 20 across the 5 of their papers we have counts for
5 papers · 1 filter
Road to scalability for efficient graph search on massively parallel neuromorphic hardware
Oskar von Seeler, Elena C. Offenberg, Carlo Michaelis +4
Efficient computation of shortest paths in weighted graphs is a fundamental problem with many applications. Neuromorphic hardware platforms promise massively parallel, efficient co…
Adding numbers with spiking neural circuits on neuromorphic hardware: A building block for future hybrid systems
Oskar von Seeler, Elena C. Offenberg, Carlo Michaelis +3
Progress in neuromorphic computing requires efficient implementation of standard computational problems, like adding numbers. Here we implement a variety of sequential and parallel…
Brian2Loihi: An emulator for the neuromorphic chip Loihi using the spiking neural network simulator Brian
Carlo Michaelis, Andrew B. Lehr, Winfried Oed +1
Developing intelligent neuromorphic solutions remains a challenging endeavour. It requires a solid conceptual understanding of the hardware's fundamental building blocks. Beyond th…
PeleNet: A Reservoir Computing Framework for Loihi
Carlo Michaelis
High-level frameworks for spiking neural networks are a key factor for fast prototyping and efficient development of complex algorithms. Such frameworks have emerged in the last ye…
Robust trajectory generation for robotic control on the neuromorphic research chip Loihi
Carlo Michaelis, Andrew B. Lehr, Christian Tetzlaff
Neuromorphic hardware has several promising advantages compared to von Neumann architectures and is highly interesting for robot control. However, despite the high speed and energy…