In this article here, the writer claims that a new type of neural net is required to deal with data that is both continuous, and also sparsely sampled.
It was my understanding that this was the entire purpose of techniques that use neural nets, to make assumptions about a system with a non-continuous data set.
So why do we need to switch to a non-layered design to deal with these data sets better?