No, they assume their peers do.

It is academia ;-)

I don't think a research paper is meant to be understood by everyone, and I imagine the authors don't have that expectation either.

I actually have the same gripe, unfortunately there is a long history of academic fields naming things like this (there’s an entire Wikipedia page on this banned after Gauss/“Gaussian” https://en.wikipedia.org/wiki/List_of_things_named_after_Car...)

Not really. There are many things named after Gauss but a "Gaussian" is almost always meant to be a probability distribution / density function that is very well understood and defined (and common)

Take a linear algebra course or read a textbook before trying to read and understand cutting edge ML research!

Rude!

Seems like they just mean the vector version of a Gaussian function: f(r) = exp(-r•r). Basically a "bell curve" except in 3D so it's a ball that's dense at the center and dies off. Then the optimizer might learn to produce an intensity, offset, and width for each point in a cloud, so the A,B,C for A*f((r-B)/C) at each point or something.

This is in fact what the optimizer does. At least in the original paper, the model learns to skew and rotate the gaussians.