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