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Have they been superseded by something else?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.
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.
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?