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And you don't have computational efficiency issues with NNs? We're also ignoring the benefits of a posterior distribution, which is useful for understanding th
by achompas 9y ago
And you don't have computational efficiency issues with NNs?
We're also ignoring the benefits of a posterior distribution, which is useful for understanding the data-generating process.
- reader5000 9y agoYeah of course. I can't explain to you why NNs outperform bayesian approaches, probably just NNs are capturing the correct type of prior for vision/language tasks. And yeah bayesian models are more interpretable but when you have millions of latent variables I'm not sure interpretability is a thing.
- achompas 9y agoYep, we arrived at my larger point: if you care about interpretability, NNs are horrible and Bayesian techniques are pretty damn great.
- reader5000 9y agoWell certainly, but interpretability is obsolete.
- achompas 9y agoNow you're just trolling. :)