> Most papers (especially the ones in deep learning) seem to also have a mathematical fetish (to put it mildly) where needless representations are used where no

> Most papers (especially the ones in deep learning) seem to also have a mathematical fetish (to put it mildly) where needless representations are used where none are required and are self evident (for example inputs belong to Real number set). It ends up making the paper pseudo complex and unapproachable. I completely disagree with that. Spelling out math is literally something out of 12th century. It just hinders understanding, if you have basic STEM-level math literacy, which anyone who reads an ML paper is implied to have (how could you seriously study linear algebra and calculus without it?). Math may actually be the first thing you recognise in a paper, which can help you cross-reference the text to understand it.