15 citations · 77 across the 20 of their papers we have counts for
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cs.NE2023★ 9 cited
The Deep Arbitrary Polynomial Chaos Neural Network or how Deep Artificial Neural Networks could benefit from Data-Driven Homogeneous Chaos Theory
Sergey Oladyshkin, Timothy Praditia, Ilja Kröker +3
Artificial Intelligence and Machine learning have been widely used in various fields of mathematical computing, physical modeling, computational science, communication science, and…
cs.NE2020
Learning Precise Spike Timings with Eligibility Traces
Manuel Traub, Martin V. Butz, R. Harald Baayen +1
Recent research in the field of spiking neural networks (SNNs) has shown that recurrent variants of SNNs, namely long short-term SNNs (LSNNs), can be trained via error gradients ju…