If any of the team working on scVI could help this query that’d be amazing.
I am just checking whether I am right in my interpretation of the base code, that the dropout occurs both in the encoder and decoder layers?
If that is the case, I just wanted to check if any internal validation works have been done on performance dependent on dropout values?
My vague understanding of VAEs (which isn’t particularly good), is that dropout isn’t necessarily a good thing? as it may affect the latent representation.
From a small trial of my data, it seems the umap embeddings look “better” when it is set to zero. I know this isn’t a good way of judging a model, but there aren’t really any consensus metrics and I find that autotune embeddings (while optimise for the lowest loss value), often result in overly smoothed umap plots where it is incredibly hard to distinguish cell types from each other.