Josh Fass

Sorry for slow response! A couple questions: * Do you have a prior defined on sigma (or log_sigma)? * Could you comment on what exactly is different between the multiple...

Nice -- thank you for starting this! I was just mentioning to @yuanqing-wang that I would benefit a lot from having a statement of the scope of this project. The...

I think there are two distinct aspects of this question: how to visually "index into" the domain of possible input graphs, and how to visualize a model's predictive uncertainty for...

Great idea! You're on a roll. I like as much as possible to have 1D or 2D examples for visualization and exploration. >I think it helps to have simple toy...

Sounds good! Plotting results for 2-parameter model like linear regression in 1D should be highly diagnostic. An approach that may be interesting for us is [[Izmailov et al., 2019] "Subspace...

Thanks for these comments and references! Your points are generally well-taken, and I agree with your point about building up from the simplest things with the most predictable performance. I...

I don't have any high-level suggestions. Reviewing the code you linked https://github.com/choderalab/pinot/blob/6785a4edc1ee2cfcd3ebd8588c8213d517ae7bea/pinot/metrics/semi_supervised.py#L37-L56, I do have a couple low-level comments: * keyword argument `k` unused (is this important?) * unsure why...

Looks fine to me, but I must admit I don't have a super clear picture where this is going at a high level. @karalets would be much better-suited to provide...

I'm not sure if the primary goal here is "approximate sampling of a posterior distribution, possibly faster than HMC" or if the goal is "find a more reliable way to...

This sounds good to me. I guess one other basic question is whether we want to have metrics for how "well-calibrated" the predictive _uncertainties_ are, and if so, what those...