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. 2022 Nov 18;4:964582. doi: 10.3389/fdgth.2022.964582

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© 2022 Kathan, Harrer, Küster, Triantafyllopoulos, He, Milling, Gerczuk, Yan, Rajamani, Heber, Grossmann, Ebert and Schuller.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Simplified overview of our (B)aseline model as well as of the three personalisation approaches used in our experiments: (T)ransfer (L)earning with shared common layers, (S)ubject-(D)ependent (S)tandardisation, and (S)ubgroup models.