Explainability of the autoencoder

[Zrrr1997]

Hi Kiru,

is there a way to explain what the autoencoder is actually learning, i.e. which visual features are important for the reconstruction of the input? An example for what I am looking for, but in the case of classification, is using the Grad-CAM approach, where you can see which regions of the image are of importance.

What would be a good approach to do this for autoencoders?