Why don't all feature selection methods in sklearn allow specifying desired variance explained?
Because PCA is just one of the feature selection methods, don't expect others to have a tractable computable formula to specify ahead of time the optimal number of new features.
I suggest to start reading on Representation learning, and what we mean by latent variables.