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Residual learning optimization

# Residual learning optimization

Dc Ae F32c32 Sana 1.1 Diffusers
MIT
DC-AE is a novel autoencoder architecture designed to accelerate high-resolution diffusion models. It maintains reconstruction quality at high spatial compression ratios through residual autoencoding and decoupled high-resolution adaptation techniques.
Image Generation
D
mit-han-lab
1,127
4
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