Sentence examples for models with weight from inspiring English sources
The siamese network consists of two convolutional neural network (CNN) models, and we train the models with weight sharing, that is, the parameters of two CNNs are the same.
Age and years of formal education were non-significant explanatory variables of weight loss at three months (age: B = 0.038, p = 0.162; formal education: B = 0.007, p = 0.922) and 12 months (age, B = 0.034, p = 0.146; formal education: B = 0.006, p = 0.922) when included in multiple regression models with weight misperception.
We will test these hypotheses with linear multiple regression models with weight or insulin resistance at 12 months as the outcomes (testing a separate model for each outcome) and arm, clinic site, and baseline patient characteristics as explanatory and control variables.
Lines give the best fit weighted linear regression models with weights given by the number of human SAR estimates.
Possible mixtures include weighted combinations of individual models, with weights to be assigned to each model according to test results.
The Average Annual Percent Change (AAPC), a weighted average of APCs from the joinpint models with weights equal to the length of the APC interval, was also computed as a summary measure of the trend over the whole observation period [ 16].
This result remains robust inalternative models with weighting by country size, clustering, and fixed effects.
Top left: proportion of correctly identified models with weights from 0.1 to 0.5 and perturbation size from 1 to 10 for RA data, using 10 spike trains.
Trigram language models were trained on both in-domain and out-of-domain datasets, where word-class mixture trigram language models with weights obtained from a procedure of forward weight adjustment were used [37].
We used both random- and fixed-effect models, with weights equal to the inverse of the variance, to calculate a summary risk estimate (DerSimonian and Laird 1986).
Where appropriate, hazard ratios were pooled in meta-analyses using random effects models, with weighting of studies according to the DerSimonian-Laird method.
