Diffusion on the Probability Simplex

Diffusion models learn to reverse the progressive noising of a data distribution to create a generative model. However, the desired continuous nature of the noising process can be at odds with discrete data. To deal with this tension between continuous and discrete objects, we propose a method of pe...

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Bibliographische Detailangaben

Hauptverfasser:	Floto, Griffin, Jonsson, Thorsteinn, Nica, Mihai, Sanner, Scott, Zhu, Eric Zhengyu
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Statistics - Machine Learning
Online-Zugang:	Volltext bestellen
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