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The first work, I linked, arguably gets around this issue completely. There we train a neural network to approximate Bayesian prediction directly. It accepts th
by ersiees 4y ago
The first work, I linked, arguably gets around this issue completely. There we train a neural network to approximate Bayesian prediction directly. It accepts the dataset as input. Thus, there is no optimisation procedure per dataset, just a forward pass. So far, this seems to be pretty stable.
- freemint 4y agoJust because you optimize network parameters to fit a surrogate model of the data doesn't mean you are not doing local optimization without guarantees on robustness or global optimality w.r.t. network parameters to fit the surrogate. Am i missing something?