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

submitted 11 months 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Have they been superseded by something else?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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[–] Sergent_Mongolito@alien.top 1 points 11 months ago (1 children)

Even though I work in developing alternate methods, I have to admit that their tutorials and vignettes are great. They also have a super reactive helpdesk. And of course, you have nice interpretable Bayesian hierarchical models, with great computational performance. If you want to noodle around with your data, give it a shot. I'm always praying them I should just work with them LOL

[–] deluded_soul@alien.top 1 points 11 months ago (1 children)

I will :) It is more of a learning exercise for me and this seems just like the kind of stuff I am looking for. There are many things in there that I probably do not know much about and it is a good learning opportunity :)

[–] Sergent_Mongolito@alien.top 1 points 11 months ago (1 children)

Cool ! By the way what kind of data do you have ? I actually work on spatio-temporal data

[–] deluded_soul@alien.top 1 points 11 months ago

It is mostly traffic flow data across the UK highways. I am trying to use it to predict traffic flows. I have seen some tutorials using this with GNNs as well.

Also interested in adding weather and event data and other things that might affect flow. So looking into solutions that can handle multivariate data, deal with missing values and also be able to handle discrete/categorical as well as continuous feature variables.