I've read plenty of theoretical computer science papers over the last 30+ years, and while some of it requires "rigorous and difficult mathematics" that is by no means universal.
I wrote my MSc thesis on the use of statistical methods for reducing error rates for OCR, and most of the papers in my literature review hardly required more than basic arithmetic and algebra.
So I stand by my statement.
Sure, there are subsets of computer science where you need more maths, just like in any field there are sub fields where you will need to understand other subjects as well, but that does not alter what I claimed.
EDIT:
Some authors are quicker to pull out the maths than others, and frankly in a lot of CS papers maths is used to obscure lack of rigor rather than to provide it. E.g the problem I ran across when writing my thesis was that once you unpacked the limited math into code you'd often reveal unstated assumptions that were less than obvious if you just read their formulas.
I wrote my MSc thesis on the use of statistical methods for reducing error rates for OCR, and most of the papers in my literature review hardly required more than basic arithmetic and algebra.
So I stand by my statement.
Sure, there are subsets of computer science where you need more maths, just like in any field there are sub fields where you will need to understand other subjects as well, but that does not alter what I claimed.
EDIT:
Some authors are quicker to pull out the maths than others, and frankly in a lot of CS papers maths is used to obscure lack of rigor rather than to provide it. E.g the problem I ran across when writing my thesis was that once you unpacked the limited math into code you'd often reveal unstated assumptions that were less than obvious if you just read their formulas.