Generative flows with invertible attentions

Flow-based generative models have shown an excellent ability to explicitly learn the probability density function of data via a sequence of invertible transformations. Yet, learning attentions in generative flows remains understudied, while it has made breakthroughs in other domains. To fill the gap...

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Main Authors: SUKTHANKER, Rhea Sanjay, HUANG, Zhiwu, KUMAR, Suryansh, TIMOFTE, Radu, VAN GOOL, Luc
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語言:English
出版: Institutional Knowledge at Singapore Management University 2022
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在線閱讀:https://ink.library.smu.edu.sg/sis_research/7612
https://ink.library.smu.edu.sg/context/sis_research/article/8615/viewcontent/01_Generative_Flows_With_Invertible_Attentions_CVPR_2022_paper.pdf
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機構: Singapore Management University
語言: English