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| Suy luận biến phân mạnh mẽ× | Tính toán Bayes xấp xỉ× | |
|---|---|---|
| Lĩnh vực≠ | Bayes | Mô phỏng |
| Họ≠ | Bayesian methods | Process / pipeline |
| Năm ra đời≠ | 2008-2018 | 2002 |
| Người khởi xướng≠ | Fujisawa & Eguchi (2008); Futami, Sato & Sugiyama (2018) | — |
| Loại≠ | Robust approximate Bayesian inference | Simulation-based Bayesian inference |
| Công trình gốc≠ | 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 ↗ | Beaumont, M.A., Zhang, W. & Balding, D.J. (2002). Approximate Bayesian Computation in Population Genetics. Genetics, 162(4), 2025-2035. DOI ↗ |
| Tên gọi khác | RVI, robust VI, outlier-robust variational Bayes, power-divergence variational inference | ABC, likelihood-free inference, simulation-based inference, Yaklaşık Bayesçi Hesaplama (ABC) |
| Liên quan≠ | 6 | 5 |
| Tóm tắt≠ | Robust variational inference (RVI) extends standard variational inference by replacing the Kullback-Leibler divergence with a divergence measure that is less sensitive to outliers and model misspecification — such as the beta-divergence or a Renyi-type divergence. This yields posterior approximations that remain well-behaved even when a fraction of the data departs from the assumed model. | Approximate Bayesian Computation (ABC) is a family of simulation-based inference methods that estimate posterior distributions without requiring an analytically tractable likelihood function. Introduced by Beaumont, Zhang and Balding (2002) in the context of population genetics, ABC replaced the intractable likelihood with repeated model simulation and a comparison of summary statistics between simulated and observed data. |
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