The other day a friend posted the following old joke about the level of rigor that mathematicians usually require. (Disclaimer: if you take the joke as a serious claim about the standards of quality in the other fields referenced in the joke, it is an obviously unfair characterization of both astronomy and physics.)

Skip all the talk and go directly to the Github Repo with code and exercises.

A few weeks ago I made a post on variational autoencoders, and how they can be applied to image generation. In this post, we’ll be taking a look at DRAW: a model based off of the VAE that generates images using a sequence of modifications rather than all at once.

We’re organizing a NIPS workshop on approximate inference. It is together with Tamara Broderick, Stephan Mandt, and James McInerney—and alongside an incredible cast of seminal researchers: David Blei, Andrew Gelman, Mike Jordan, and Kevin Murphy. [Workshop homepage]

Earlier this week, RStudio announced sparklyr, a new package that provides an interface between R and Apache Spark. We republish RStudio’s blog post below (see original) for your convenience.

ROC Curve