I’m trying to figure out how can weighted MMD from Weighted Maximum Mean Discrepancy for Unsupervised Domain Adaptation (chapter 3. Weighted Maximum Mean Discrepancy) be adapted for InfoVAE: A Tutorial on Information Maximizing Variational Autoencoders.

First one is written in some “unbiased approximation to MMD with linear complexity” terms but the second one is written with “kernel embedding trick” terms.

I guess some info can be found in original papers: A Kernel Two-Sample Test (about terms from weighted MMD article) and A Kernel Method for the Two-Sample Problem (presumably original article on MMD) but that a bit too much for me.

I would appreciate any ideas on how to adapt this for InfoVAE.