Robust Bayesiansk Inferens
Robust Bayesiansk Inferens (RVI) udvider standard Bayesiansk inferens ved at erstatte Kullback-Leibler-divergensen med et divergensenmål, der er mindre følsomt over for outliers og model-fejspecificering — såsom beta-divergensen eller en Renyi-type divergens. Dette giver posterior-approksimationer, der forbliver velfungerende, selv når en brøkdel af dataene afviger fra den antagne model.
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Method map
The neighbourhood of related methods — select a node to explore.
Kilder
- 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 ↗
Sådan citerer du denne side
ScholarGate. (2026, June 3). Robust Variational Inference. ScholarGate. https://scholargate.app/da/bayesian/robust-variational-inference
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Approksimativ Bayesiansk BeregningSimulering↔ compare
- Bayesiansk regressionBayesiansk↔ compare
- Markov Chain Monte Carlo (MCMC)Simulering↔ compare
- Robust Bayesiansk InferensBayesiansk↔ compare
- Robust Markovkæde Monte CarloBayesiansk↔ compare
- VariationsinferensBayesiansk↔ compare
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