ライフサイエンスコーパス: maximum a posteriori

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1 maximization (3DOSEM) and the 3-dimensional maximum a posteriori (3DMAP).

2 The application of a maximum-a-posteriori Bayesian inference method identifie

3 stimulus integration, we used nonparametric maximum a posteriori decoding to compare the ability of

4 takes-all (WTA) models and a Bayesian model, maximum a posteriori estimate (MAP), to determine which

5 We calculated maximum a posteriori estimates of song spectrograms usin

6 clique potential functions in the MRF so its maximum a posteriori estimation can be reduced to the we

7 Further, as an extension, maximum a posteriori estimation is provided.

8 entation to segment the minimum distance and maximum a posteriori estimation to infer de novo CNVs fr

9 Coupled with segmentation and maximum a posteriori estimation, our algorithm compares

10 ithm aims at robustness by using a priorless maximum a posteriori estimator and at efficiency by a dy

11 s used to analyze the parametric behavior of maximum a posteriori inference calculations for graphica

12 round model alleviates the drawbacks of MAP (maximum a posteriori log likelihood) scores.

13 n correction and a two-dimensional iterative maximum a posteriori (MAP) algorithm using attenuation c

14 e estimation process of parameters through a maximum a posteriori (MAP) Bayesian method to facilitate

15 We obtained very high Maximum a Posteriori (MAP) classification with a mixture

16 Maximum a posteriori (MAP) common secondary structures,

17 tions on the time-frequency plane that yield maximum a posteriori (MAP) spectral estimates that are c

18 e reconstructed with the fully 3-dimensional maximum a posteriori method, and CT images were reconstr

19 e done in linear time using forward-backward maximum-a-posteriori methods.

20 The method follows a maximum a posteriori principle to form a novel network s

21 iterative reconstruction algorithm utilizing maximum-a-posteriori principles and integrating the stat

22 ng randomized data to determine the critical maximum a posteriori probability (MAP) values for statis

23 s expectation maximization and 3-dimensional maximum a posteriori probability (MAP3D) algorithms.

24 dexamethasone plasma concentrations by using maximum a posteriori probability estimation; we evaluate

25 The software is also capable of maximum a posteriori probability image estimation (MAP-S

26 e, i.e., that best "explains" it, called the maximum a posteriori skeleton.

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