Somewhat related — I’d love to hear your thoughts on dex-Lang and Haskell for array programming?

I still am excited by Dex (https://github.com/google-research/dex-lang/) and still write code in it! I have a bunch of demos and fixes written, and am just waiting for Dougal to finish his latest re-write before I can merge them.

why (if) was this not picked for further research? i know that oatml did quite amount of work on this front as well and it seems the direction is still being worked on. want to get ur 2 cent on this approach.

BNNs certainly have their uses, but I think people in general found that it's a better use of compute to fit a larger model on more data than to try to squeeze more juice from a given small dataset + model. Usually there is more data available, it's just somewhat tangentially related. LLMs are the ultimate example of how training on tons of tangentially-related data can ultimately be worthwhile for almost any task.

just a little typo, but it's Kullback-Leibler.

Thanks for pointing that out!

What did you use to produce the article? I really really like the formatting.

I think we used a distill.pub template. Also Jerry wrote some custom BNN fitting code in javascript. I'll ask my co-authors to open-source it.

Update: the code is here:

https://github.com/jerryqhyu/distill_bayes_net