Neural-Process-Family
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LNP 1d regression marginal predictive
Do you have code for evaluating the marginal predictive in the case of LNPs for the 1d regression scenario? By this I mean combining the latent samples giving a single mean and variance. I suppose this should be given by the law of total variance. Something like figure 3 here
I managed to write this code myself so this issue can be closed.