Information compression for variable input size

Is there a way to compress information of a variable input size?

Autoencoder requires standardized input sizes. Although I can add masks on the cost function and add dummy features to standardize input/output size, I am hesitant with the potential drawbacks.

The input structures I am interested in are graphs and images. If input sizes and shapes vary too much, padding, resizing and rescaling do not work.

Topic feature-reduction autoencoder machine-learning

Category Data Science

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