# Learning Bayesian Deep Learning, Uncertainty & Variational Techniques

### What am I working on now? Discussions are Welcome!

• Interpreting p(y\|x)$p(y\|x)$ and modelling example weighting

• Going to stop treating p(y\|x)$p(y\|x)$ as a classfication confidence metric, since it is determinstic. p(y\|x)$p(y\|x)$ is not for deciding whether certain or uncertain.

• p(y\|x)$p(y\|x)$ is good as a metric of whether x matches y, though not a good metric indicating whether x is blur or not.

• Utilities of Uncertainties