Variational Potential Flow: A Novel Probabilistic Framework for Energy-Based Generative Modelling

Energy based models (EBMs) are appealing for their generality and simplicity in data likelihood modeling, but have conventionally been difficult to train due to the unstable and time-consuming implicit MCMC sampling during contrastive divergence training. In this paper, we present a novel energy-bas...

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Veröffentlicht in:	arXiv.org 2024-07
Hauptverfasser:	Junn Yong Loo, Adeline, Michelle, Pal, Arghya, Baskaran, Vishnu Monn, Chee-Ming, Ting, Phan, Raphael C -W
Format:	Artikel
Sprache:	eng
Schlagworte:	Datasets Density Energy Evolution Image processing Potential energy Potential flow Sampling
Online-Zugang:	Volltext
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