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Dynamic neural manifolds for flexible closed-loop control on neuromorphic hardware
Oskar von Seeler, Christian Tetzlaff, Andrew Lehr
In biological circuits, sequential neural activity evolves along dynamic, low-dimensional manifolds to enable flexible behavior. Spiking network models link aspects of this sequent…
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…