Max Balandat

I like this design! > It doesn't do anything about DeterministicModels. Those will still need to deal with their own transforms, which is not implemented here. If we make Model...

If I understand this issue correctly, this is not a bug. Note that the acquisition value of a `q`-batch when doing joint optimization (`sequential=False`) is indeed a joint value, that...

> The documentation [here](https://botorch.org/api/optim.html#module-botorch.optim.optimize) suggests that the returned score is a q-dim vector, i.e. a score for each generated candidate. Not quite, this is what the documentation says: > a...

Hmm interesting it might be that some of the input transformations may not play well with the `condition_on_observations` call? @saitcakmak you've probably got the best understanding of the input transforms,...

I assume this works fine if you don't use an input transform?

Yeah I think it's just too noisy to say much - and running a proper comparison with a lot of iterations is a bit too costly to run as a...

Hmm good question. Sobol (and QMC methods in general) don't really play well with non-box bounds and non-continuous parameters. I would recommend just drawing those parameters independently at random and...

So one thing to note is that if you define the parameter as an integer in Ax itself, we'll try to model it as a numerical parameter; i.e. we'll assume...

Sorry this docs failure isn't exactly actionable - you'll have to add an entry to this json file to link it on the website: https://github.com/pytorch/botorch/blob/main/website/tutorials.json Speaking of the tutorial -...

Thanks for tying up all the loose ends. One more outstanding issue: The tutorial is pretty heavyweight, so it'll cause some issues for the CI. We usually use a `SMOKE_TEST`...