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[D] Are neural processes still relevant? (alien.top)

submitted 2 years ago by deluded_soul@alien.top to c/machinelearning@academy.garden

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There was some hype around neural processes which seem like a marriage between non-parametric models like GPs and NN but have not heard anything about them recently.

Have they been superseded by something else? I have some spatio temporal data that I am looking to play with and wonder if this is a good way to dive into them but want to convince myself that they are still a somewhat relevant family of models to spend time on.

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[–] lolillini@alien.top 1 points 2 years ago (1 children)

It's weird that so many folks in the comments worked with GPs and NNs and never heard of neural processes. They were a big deal until a few years ago: https://yanndubs.github.io/Neural-Process-Family/text/Intro.html

Here is the issue with neural processes: they suck, they really do, on any reasonable real-world problem beyond the simple examples with tons of training data in relatively simple domains. Source: a frustrated grad student who spent hours making conditional neural processes work on a real-world problem.

[–] deluded_soul@alien.top 1 points 2 years ago

Thank you. Good to hear about your experience.

So GNNs are the alternative or do you know about something else which might be interesting to look at?