Sam Daulton

Hi @Abrikosoff, I am guessing that @Balandat intended to the constraint model to be pretrained outside of Ax. If you wanted to use non-linear constraints with scipy, you could implement...

Yes that's right. If you need a trained model from Ax, using data collected during the experiment, I would recommend going with one of the two approaches that I mentioned,...

> 1. You'd want to construct a subclass of qLogEI that takes in, for example, a list of `high_prob_constraints` that would be treated differently than in addition to typical constraints....

@vmallela0, the setting closure would need to passed to `register_prior` (in the link in the comment above: here https://github.com/cornellius-gp/gpytorch/blob/d171863c50ab16b5bfb7035e579dcbe53169e703/gpytorch/kernels/index_kernel.py#L71) when the prior is "registered" on the gpytorch Module. Here are...

Late to the game here, but implementing analytic PoI under the common assumption of independent objectives would also be easy to do

> in most cases the there are only 3 to 4 important solvents Is it bad if the suggest arms include more than 3-4 or is this just prior knowledge...

Did you see similar degradation in 1.0.0 using `method="fast"`?

Are these results for 1.0.0 using "fast" or balanced? Are you supplying objective thresholds for the 1.0.0 optimization?

Also, what does your optimization loop look like for generating arms and reporting evaluations with the client?

Hi @davifebba! It seems like using TimeAsFeature would work here. Although this uses the start time/duration as a contextual variables, the start time/duration should just be the device age with...