M. Nikitina

Spectral characteristics of autoencoder parameters as a vector representation of data

Experimental results suggest that the parameters of trained autoencoders can be viewed as sample representations, allowing for a high degree of accuracy in distinguishing between models trained on different data subsets, without resorting to complex vector generation algorithms or using the original samples.