Exploring the training of residual networks under differential privacy (DP). Development of an architectural adaptation for residual networks that increases the validation accuracy when trained with DP called ScaleNorm.
This is a selection of scripts written for my Master's Thesis. I conducted this work at the Medicine in AI at the Technical University of Munich. This paper is a short version of the thesis.