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Have they been superseded by something else?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.
Never heard of neural processes. If you mean deep architectures based on Gaussian Processes (such as Deep GPs or Deep Kernel Learning), does are very much SotA in applied AI for information-restricted domains or in scenarios where you really need a proper uncertainty treatment (such as medical trials, investment banking/corporate finance, datacenter resource allocation and webpage optimization to name a few).
But I am not sure if that answers your question
It was from a paper from Deep Mind in 2018, Ganelo et al.