March 14, 2024, 4:42 a.m. | Marcus H\"aggbom, Morten Karlsmark, Joakim and\'en

cs.LG updates on

arXiv:2403.08362v1 Announce Type: cross
Abstract: Microcanonical gradient descent is a sampling procedure for energy-based models allowing for efficient sampling of distributions in high dimension. It works by transporting samples from a high-entropy distribution, such as Gaussian white noise, to a low-energy region using gradient descent. We put this model in the framework of normalizing flows, showing how it can often overfit by losing an unnecessary amount of entropy in the descent. As a remedy, we propose a mean-field microcanonical gradient …

abstract arxiv cs.lg distribution energy entropy framework gradient low low-energy mean noise samples sampling type white noise

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