Note that instrumentally, there is little difference, according to Jaynes himself:
For example our system of probability could hardly, in style, philosophy, and purpose, be more different from that of Kolmogorov.
[...]
Yet when all is said and done we find ourselves, to our own surprise, in agreement with Kolmogorov and in disagreement with his critics, on nearly all technical issues.
By "technical issues" I think that Jaynes means the measure theory basis of probability, not the everyday applications of statistics.
EDIT: And he's comparing Kolmogorov's definition of probability (which starts with a set of possible outcomes and then treats events as subsets) to his own view (IIRC he thinks you can calculate with events directly and need no underlying set). He's not comparing Frequentism and Bayesianism.
Question in title.
This is obviously subjective, but I figure there ought to be some "go-to" paper. Maybe I've even seen it once, but can't find it now and I don't know if there's anything better.
Links to multiple papers with different focus would be welcome. For my current purpose I have a preference for one that aims low and isn't too long.