1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Predicting Wall Thickness Changes in Cold Forging Processes: An Integrated FEM and Neural Network approach
Sasa Ilic, Abdulkerim Karaman, Johannes Pöppelbaum +3
This study presents a novel approach for predicting wall thickness changes in tubes during the nosing process. Specifically, we first provide a thorough analysis of nosing processe…
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…