Sentence examples for a diagonal model from inspiring English sources

Exact(1)

As mentioned in Section 2.2 (cf. Eq. (15)), we use a diagonal model covariance matrix C d, containing the squared uncertainties of the internal coefficients, which are also recovered by the CI.

Similar(59)

Each dataset was analysed using the methods described in Section 2. A simple diagonal model for and failed to detect the presence of non-additive genetic variance at five of the 14 sites, so these were fixed to zero.

Reluctantly, I tore myself away from the WS55807 and set my sights on its 4 3 aspect ratio cousin, a 50-inch (diagonal) model that had essentially the same high-definition specs but with a square screen.

The i-supervector extractor can be implemented by adopting the diagonal modeling part of the JFA [12],[24] with a slight modification: the diagonal model D is trained per utterance instead of per speaker basis in order to capture both speaker and session variability.

Another difference between the two load cases is that upon reaching approximately half the design load, the diagonal model starts exhibiting a stiffer response than the perpendicular load case.

We again used LRTs to determine statistical support for mutational covariance between two traits, comparing the log-likelihood of the unconstrained model (in which covariance was estimated) with that of a model where the covariances were constrained to zero, and only the two individual trait variances were estimated (a diagonal matrix model).

As proposed in [24], the initial iterations use a diagonal covariance model that serves to make the posterior probability calculation (6) feasible.

The diagonal model focusing on the interactions between researchers, policymakers and lay people has been noted to be complex [ 4, 5].

To this end, we compare the citation distribution for all pairs of years using the Kolmogorov-Smirnov test and fit a box-diagonal model to the matrix of p-values.

The target equilibrium point is an analogous of the focal point defined in a class of piecewise linear diagonal models [34] (see next section).

Efficient parametrization is achieved by performing several optimization techniques such as state splitting, k-means based initialization, scaling reduction, equivalent diagonal models, and compiler optimizations.

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