I’d like to know what the advantage is over KL divergence. It seems like the important idea is symmetry? Not clear to me why that matters; I’d love to know what application this is used for.
I was just reading about JSD the other day after reading about KL divergence...seems like a nifty measurement device for things like sim-to-real evaluations in robots (the reason I was going down this rabbit hole.)
I think the appeal over raw KL is that JSD behaves a bit nicer when the simulated and real distributions don't perfectly overlap...which is basically always true in the real world!
This looks interesting and I'm curious if anyone has more context for why it's on the frontpage today.
Every now and then, a random math or science concept hits front page. Usually, people chime in with interesting perspectives on it. Guess we'll see.
I’d like to know what the advantage is over KL divergence. It seems like the important idea is symmetry? Not clear to me why that matters; I’d love to know what application this is used for.
The Hacker News hive mind is real!
I was just reading about JSD the other day after reading about KL divergence...seems like a nifty measurement device for things like sim-to-real evaluations in robots (the reason I was going down this rabbit hole.)
I think the appeal over raw KL is that JSD behaves a bit nicer when the simulated and real distributions don't perfectly overlap...which is basically always true in the real world!