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[D] Normalizing flows for distributions with finit support
Jan. 5, 2022, 3:59 p.m. | /u/likan_blk
Machine Learning www.reddit.com
I need to learn a map from Gaussain distribution to Gamma distribution with some custom parameters. So for both distributions, I can sample and evaluate probability density. The first thing, that came to my mind is using normalizing flow.
Most approaches include log target probability density evaluation in the loss function. Obviously, normalizing flow sometimes returns negative values, and this term equals to infinity. "Positivation" functions on top of the NF break bijection properties for some regions of space (if …
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