17 citations · 55 across the 15 of their papers we have counts for
12 papers · 1 filter
Equivalence of approximation by networks of single- and multi-spike neurons
Dominik Dold, Philipp Christian Petersen
In a spiking neural network, is it enough for each neuron to spike at most once? In recent work, approximation bounds for spiking neural networks have been derived, quantifying how…
Reconfiguration of pivoting cube ensembles under local sensing constraints using geometric deep learning
Nadezhda Dobreva, Emmanuel Blazquez, Jai Grover +3
We demonstrate that local sensing is sufficient for effective global reconfiguration of homogeneous pivoting cube modular robots in two dimensions. While cube selection (i.e., whic…
Energy efficiency analysis of Spiking Neural Networks for space applications
Paolo Lunghi, Stefano Silvestrini, Dominik Dold +3
While the exponential growth of the space sector and new operative concepts ask for higher spacecraft autonomy, the development of AI-assisted space systems was so far hindered by…
Causal pieces: analysing and improving spiking neural networks piece by piece
Dominik Dold, Philipp Christian Petersen
We introduce a novel concept for spiking neural networks (SNNs) derived from the idea of "linear pieces" used to analyse the expressiveness and trainability of artificial neural ne…
Stable Learning Using Spiking Neural Networks Equipped With Affine Encoders and Decoders
A. Martina Neuman, Dominik Dold, Philipp Christian Petersen
We study the learning problem associated with spiking neural networks. Specifically, we focus on spiking neural networks composed of simple spiking neurons having only positive syn…
Scalable Network Emulation on Analog Neuromorphic Hardware
Elias Arnold, Philipp Spilger, Jan V. Straub +4
We present a novel software feature for the BrainScaleS-2 accelerated neuromorphic platform that facilitates the partitioned emulation of large-scale spiking neural networks. This…