Max Balandat
Max Balandat
The awesomeness of this is totally awesome.
This is something that I'd like as well, let me see if I can find some time to work on this this week.
@Galto2000 I'm assuming what you'd like to do here is provide the noise for the different tasks, but not the cross-task covariance - this should still be inferred. Is this...
FWIW, I put up an early draft for this in 49e810b1a4f29fe1e0a102ad6f5963e90ae0dbdd - will have to do some cleaning up and testing before I make this a PR.
Hmm, I'm realizing that the fact that `MultitaskMultivariateNormal` can be using either interleaved or non-interleaved representation significantly complicates things here. It'll take a little bit of work to iron this...
It seems that we should address #539 first in order to make this less of a pain to implement.
yeah basically if you have `n` points and `t` tasks, gpytorch represents the joint covariance as an `nt x nt` matrix. You can represent that in different ways, either `K_{data}...
@Galto2000 sorry I haven't gotten to work much on this - the draft isn't really in a usable state at this point, so unless you plan on actively developing it's...
@wjmaddox, @qingfeng10 I know you are/were thinking about this in as well. Are you working on this / planning to work on this in the near future?
I suspect this might be due to the 3080 in PyTorch using tf32 by default, which has lower precision than FP32 and so computations just aren’t accurate enough. Try disabling...