$\alpha$-VAEs : Optimising variational inference by learning data-dependent divergence skew

no code implementations • ICML Workshop INNF 2021 • Jacob Deasy, Tom Andrew McIver, Nikola Simidjievski, Pietro Lio

The {\em skew-geometric Jensen-Shannon divergence} $\left(\textrm{JS}^{\textrm{G}_{\alpha}}\right)$ allows for an intuitive interpolation between forward and reverse Kullback-Leibler (KL) divergence based on the skew parameter $\alpha$.

Denoising Variational Inference