Deepmind conditional neural process: evaluation
$begingroup$
Going through the Deepmind jupyter notebook conditional neural processes, the plots at the bottom of the notebook show that the ground truth and the predicted distribution only overlap around the "context points". These context points are already in the training set. This comes as a surprise to me because I was expecting that if the model worked, then the ground truth curve would lie inside the predicted distribution at non-context points. So, doesn't this mean that the network failed to model the data? If that's the case, what's the value being shown here?
Edit: looking at Fig 2 in their arxiv publication here and comparing them with the plots in the jupyter notebook, it seems that the publication shows nice plots for which this worked. The plots in the notebook are not as confirming though.
gaussian deepmind
asked 7 mins ago
shadishadi
15314
$endgroup$
add a comment |
$begingroup$
Going through the Deepmind jupyter notebook conditional neural processes, the plots at the bottom of the notebook show that the ground truth and the predicted distribution only overlap around the "context points". These context points are already in the training set. This comes as a surprise to me because I was expecting that if the model worked, then the ground truth curve would lie inside the predicted distribution at non-context points. So, doesn't this mean that the network failed to model the data? If that's the case, what's the value being shown here?
Edit: looking at Fig 2 in their arxiv publication here and comparing them with the plots in the jupyter notebook, it seems that the publication shows nice plots for which this worked. The plots in the notebook are not as confirming though.
gaussian deepmind
asked 7 mins ago
shadishadi
15314
$endgroup$
add a comment |
$begingroup$
Going through the Deepmind jupyter notebook conditional neural processes, the plots at the bottom of the notebook show that the ground truth and the predicted distribution only overlap around the "context points". These context points are already in the training set. This comes as a surprise to me because I was expecting that if the model worked, then the ground truth curve would lie inside the predicted distribution at non-context points. So, doesn't this mean that the network failed to model the data? If that's the case, what's the value being shown here?
Edit: looking at Fig 2 in their arxiv publication here and comparing them with the plots in the jupyter notebook, it seems that the publication shows nice plots for which this worked. The plots in the notebook are not as confirming though.
gaussian deepmind
asked 7 mins ago
shadishadi
15314
$endgroup$
Going through the Deepmind jupyter notebook conditional neural processes, the plots at the bottom of the notebook show that the ground truth and the predicted distribution only overlap around the "context points". These context points are already in the training set. This comes as a surprise to me because I was expecting that if the model worked, then the ground truth curve would lie inside the predicted distribution at non-context points. So, doesn't this mean that the network failed to model the data? If that's the case, what's the value being shown here?
Edit: looking at Fig 2 in their arxiv publication here and comparing them with the plots in the jupyter notebook, it seems that the publication shows nice plots for which this worked. The plots in the notebook are not as confirming though.
gaussian deepmind
gaussian deepmind
asked 7 mins ago
shadishadi
15314
asked 7 mins ago
shadishadi
15314
edited 1 min ago
shadi
asked 7 mins ago
shadishadi
15314
asked 7 mins ago
shadishadi
15314
asked 7 mins ago
shadishadi
15314
15314
add a comment |
add a comment |
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