CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models

Yang Mengyue
Yang Mengyue
Liu Furui
Liu Furui
Chen Zhitang
Chen Zhitang
Shen Xinwei
Shen Xinwei
Wang Jun
Wang Jun
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Abstract:

Learning disentanglement aims at finding a low dimensional representation which consists of multiple explanatory and generative factors of the observational data. The framework of variational autoencoder (VAE) is commonly used to disentangle independent factors from observations. However, in real scenarios, factors with semantics are no...More

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