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cs.NE2026
Upper bounds on the number of causal pieces in spiking neural networks
Dominik Dold, Dennis Elbrächter, Philipp Petersen
The input space of single-spike neural networks decomposes into causal pieces, and the number of causal pieces has been shown to provide a lower bound on the approximation error fo…
cs.NE2026
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…
cs.NE2025
Sustainable AI: Mathematical Foundations of Spiking Neural Networks
Adalbert Fono, Manjot Singh, Ernesto Araya +3
Deep learning's success comes with growing energy demands, raising concerns about the long-term sustainability of the field. Spiking neural networks, inspired by biological neurons…