Machine learningDeep learning / NLP / CV
域自适应变分自编码器
域自适应变分自编码器（DA-VAE）扩展了标准的VAE框架，用于学习解耦的潜在表示，将特定于域的变化与与类别相关且与域无关的内容分离开来，从而使在源域上训练的模型能够有效地泛化到具有有限或无目标标签的不同但相关的目标域。
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来源
- Ilse, M., Tomczak, J. M., Louizos, C., & Welling, M. (2020). DIVA: Domain Invariant Variational Autoencoders. Proceedings of the Third Conference on Medical Imaging with Deep Learning (MIDL 2020), PMLR 121, 322–348. link ↗
- Kingma, D. P., & Welling, M. (2014). Auto-Encoding Variational Bayes. Proceedings of the 2nd International Conference on Learning Representations (ICLR 2014). link ↗
如何引用本页
ScholarGate. (2026, June 3). Domain-Adaptive Variational Autoencoder (DA-VAE). ScholarGate. https://scholargate.app/zh/deep-learning/domain-adaptive-variational-autoencoder
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