That’s an interesting link. It sound like the results can only be applied to strictly Bayesian methods though, so they couldn’t be applied to neural networks as they exist now.
There is some progress in that direction though. The bigger problem, as mentioned in the link, it is that that estimator seems to completely break down if you try and use an approximation to the posterior although there seems to be ongoing work to estimate generalisation error just from MCMC samples.
That’s an interesting link. It sound like the results can only be applied to strictly Bayesian methods though, so they couldn’t be applied to neural networks as they exist now.
There is some progress in that direction though. The bigger problem, as mentioned in the link, it is that that estimator seems to completely break down if you try and use an approximation to the posterior although there seems to be ongoing work to estimate generalisation error just from MCMC samples.