Gott & al. have a decent basic concept, but a highly questionable implementation of the idea. (At least, in the paper of theirs I looked at from a few years ago

Gott & al. have a decent basic concept, but a highly questionable implementation of the idea. (At least, in the paper of theirs I looked at from a few years ago; this might be a slightly different one.) They optimize for least squares distance errors for all pairs of distances across the map, but they consider points which are at opposite sides of a map across a discontinuity (but nearby on the globe) to have extremely high error, and therefore their optimization routine radically tugs those points towards each-other. The result is really scrunched up edges. They'd get dramatically better results by either (a) ignoring very distant points altogether, (b) figuring out how to measure distance across a discontinuity, or (c) comparing distances on the map to distances on the globe if you go the "long way" around, i.e. following a similar path to the one implied to be shortest by the map.