1 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.LG2024★ 1 cited
Improving Quaternion Neural Networks with Quaternionic Activation Functions
Johannes Pöppelbaum, Andreas Schwung
In this paper, we propose novel quaternion activation functions where we modify either the quaternion magnitude or the phase, as an alternative to the commonly used split activatio…
cs.LG2024★ 1 cited
Time Series Compression using Quaternion Valued Neural Networks and Quaternion Backpropagation
Johannes Pöppelbaum, Andreas Schwung
We propose a novel quaternionic time-series compression methodology where we divide a long time-series into segments of data, extract the min, max, mean and standard deviation of t…
cs.LG2022
Quaternion Backpropagation
Johannes Pöppelbaum, Andreas Schwung
Quaternion valued neural networks experienced rising popularity and interest from researchers in the last years, whereby the derivatives with respect to quaternions needed for opti…