Bayesian methodsBayesian / computational
鲁棒变分推断
鲁棒变分推断（RVI）通过用对离群值和模型误设不敏感的散度度量（例如 beta 散度或 Renyi 型散度）替换 Kullback-Leibler 散度来扩展标准变分推断。这会产生即使在数据的一部分偏离假设模型时也能保持良好行为的后验近似。
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来源
- Futami, F., Sato, I. & Sugiyama, M. (2018). Variational inference based on robust divergences. Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 84:813-822. link ↗
- Ghosh, S. & Basu, A. (2016). Robust Bayes estimation using the density power divergence. Annals of the Institute of Statistical Mathematics, 68(2), 413-437. link ↗
如何引用本页
ScholarGate. (2026, June 3). Robust Variational Inference. ScholarGate. https://scholargate.app/zh/bayesian/robust-variational-inference
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