Here is what I learned on the second day of the nips workshops where I went to the deep bayesian networks workshops.

I feel like I should take a second to define precisely what the workshop is about. In a nutshell, it’s about trying to combine Bayesian methods and deep neural networks. On paper this seems like a great idea to augment Bayesian methods with the flexibility of neural networks. However, it is a path that really emphasizes the key weakness of Bayesian methods: the fact that it is riddled with computational problems.

The initial idea that people have been using to deal with the computational problems is “variational inference” (minimizing the “reverse” Kullback-Leibler divergence )

The two highlights of the day were a first talk by Zoubin Ghahramani who gave a nice history lesson on Bayesian neural networks. We do tend to get a little bit caught up in what we are doing, and it’s great to have these talks from time to time to remember the giants whose shoulders we are standing on. The second highlight was a tribute to one of those giants, David Mackay who passed away earlier during the year, by Ryan Adams. I didn’t know Prof. Mackay, but this was a very moving talk and it painted a very vivid picture of him. He seemed like a great guy, and an even greater scientist. He will be missed.

An intriguing idea (which was presented several times during the whole conference) was entitled “Stein variational inference”. It consists in finding a cloud of points to approximate a target probability distribution according to an objective that is reminescent of . I’m not sure how much this differs from using a sparse kernel-based approximation of the log probability of the target distribution. They also had a deep network method that was reminescent of generative adverserial networks.

This has a lot of interesting flavor with the combination of Stein’s method and variational inference and kernel-methods so I definitely need to look at it further

At this point, I was pretty saturated so I just couldn’t follow anymore, but the panel discussion which closed the workshop was pretty great. I’m guessing that these panels are growing on me after all. I really didn’t like them last year at nips, as well as the few that were in the cosyne workshops (I remember one at cosyne that was particularly unproductive). It really depends on the panel and the public’s comment… but it can be great. Overall, I liked the first day of the workshops more, but I’m guessing that, quite simply, that workshop simply aligned a bit more with my interests than today’s one. It was still great though.