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Diffusion Model with Cross Attention as an Inductive Bias for Disentanglement

Disentangled representation learning strives to extract the intrinsic factors within observed data. Factorizing these representations in an unsupervised manner is notably challenging and usually requires tailored loss functions or specific structural designs.

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Cite this as

Tao Yang, Cuiling Lan, Yan Lu, Nanning zheng (2024). Dataset: Diffusion Model with Cross Attention as an Inductive Bias for Disentanglement. https://doi.org/10.57702/xwue9zz1

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Additional Info

Field	Value
Created	December 3, 2024
Last update	December 3, 2024
Defined In	https://doi.org/10.48550/arXiv.2402.09712
Author	Tao Yang
More Authors	Cuiling Lan Yan Lu Nanning zheng