"Rescaling Intermediate Features Makes Trained Consistency Models Perform ..."

Junyi Zhu et al. (2024)

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DOI: —

access: open

type: Conference or Workshop Paper

metadata version: 2024-07-26

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  - electronic edition @ openreview.net (open access)
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  dblp key:
  - conf/iclr/00020LNB24
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  persistent URL:
  - https://dblp.org/rec/conf/iclr/00020LNB24
Junyi Zhu, Zinan Lin, Enshu Liu, Xuefei Ning, Matthew B. Blaschko:
Rescaling Intermediate Features Makes Trained Consistency Models Perform Better. Tiny Papers @ ICLR 2024

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