Comments (3)
vdutor
commented on August 27, 2024
Hi @dtchang, I had another look at the notebook and I think the fit is actually pretty good. In this PR, I updated the notebook so that it plots the mean and variance of y instead of f. In the figure below, you can see that the fit now encloses the data. You can also observe the increased uncertainty on f in the far left and right of the domain.
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dtchang
commented on August 27, 2024
Vincent,
If so, that will be great. I can’t find the updated notebook in the GitHub. Please send it to me or update the GitHub asap. Thanks.
Regards,
Dan
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From: Vincent Dutordoir
Sent: Tuesday, August 3, 2021 6:23 AM
To: secondmind-labs/GPflux
Cc: dtchang; Mention
Subject: Re: [secondmind-labs/GPflux] GPLayer's prediction seems to be tooconfident (#37)
Hi @dtchang, I had another look at the notebook and I think the fit is actually pretty good. In this PR, I updated the notebook so that it plots the mean and variance of y instead of f. In the figure below, you can see that the fit now encloses the data. You can also observe the increased uncertainty on f in the far left and right of the domain.
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dtchang
commented on August 27, 2024
I still can't find the updated notebook in the GitHub. But, I think this issue should be re-opened because it is not a plotting problem, but a prediction problem. f is the prediction, whereas y is the target. So, it seems to me the plot should be based on the mean and variance of f, not y, as in the published tutorial. BTW, the issue of poor uncertainty estimation exists not just in this tutorial, but also in other tutorials (e.g., "Introduction to GPflux" and "Why GPflux is a modern (deep) GP library").
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Related Issues (20)
- Clean up BayesianDenseLayer
- Attempting to learn models with multidimensional inputs leads to an error. HOT 6
- Optimisation problem in gpflux HOT 1
- Enquiry about model.predict() with batch_size and sampling from each layer after model fitting
- Usage of NatGradModel/Wrapper to train variational parameters
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- Customize NatGrad Model to turn off variational parameters in hidden layers HOT 3
- ModelCheckpoint with save_weights_only=False crashes HOT 3
- GPflux for text classification? HOT 2
- Bug when computing the mean of marginal variational q(f) HOT 3
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