Machine learningDeep learning / NLP / CV
半监督扩散模型
半监督扩散模型将去噪扩散概率框架扩展到仅有部分训练样本带有类别标签的设置中。通过将无条件扩散主干与在标记示例上训练的轻量级分类器相结合，它可以在利用无标记数据结构的同时，学习生成高质量、标签条件化的输出。
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来源
- Sohl-Dickstein, J., Weiss, E., Maheswaranathan, N., & Ganguli, S. (2015). Deep Unsupervised Learning using Nonequilibrium Thermodynamics. Proceedings of the 32nd International Conference on Machine Learning (ICML), 2256–2265. link ↗
- Ho, J., Jain, A., & Abbeel, P. (2020). Denoising Diffusion Probabilistic Models. Advances in Neural Information Processing Systems (NeurIPS), 33, 6840–6851. link ↗
如何引用本页
ScholarGate. (2026, June 3). Semi-supervised Diffusion Model for Generative Learning with Partial Labels. ScholarGate. https://scholargate.app/zh/deep-learning/semi-supervised-diffusion-model
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