We'd like to know the posterior probability distribution, a distribution that captures possible uncertainties we have about our model or data. |
Fundamentally, Bayesian inference uses a prior distribution to estimate posterior probabilities. Bayesian inference is an important technique in statistics, and ... Bayesian inference in phylogeny · Dutch book theorems · Marginal likelihood |
| Байесовский вывод |  |
Байесовский вывод — статистический вывод, в котором свидетельство и/или наблюдение используются, чтобы обновить или вновь вывести вероятность того, что гипотеза может быть верной; название байесовский происходит от частого использования в процессе... Википедия
10 июл. 2023 г. · Posterior probability, in the context of Bayesian inference, refers to the probability of a hypothesis or an event given observed data. |
Specifically, the posterior predictive pmf calculates the overall chance of observing [Math Processing Error] Y ′ = y ′ across all possible [Math Processing ... |
The Bayesian approach provides us with a posterior probability distribution of the quantity of interest. We are free to summarize that distribution in any way ... |
In this paper, we present regularized Bayesian inference (RegBayes), a novel computational frame- work that performs posterior inference with a regularization ... |
29 окт. 2024 г. · We propose to refine flows with additional control signals based on a simulator. Control signals can include gradients and a problem-specific ... |
11 июн. 2024 г. · Posterior inference with diffusion priors poses an intractable inference problem, where prior work has proposed methods for approximate inference. |
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