5 with theoretical density f1(Cox(2,3,0.05)) (resp. f2(Weibull(1.2,2))), that the error, being important at the start, decreases speedily for the values of ϵ in the neighborhood of the lower bound. This may be explained by the fact that they are at the boundary of the stability...
The training samples are 200 windows of four observations, which we select by the kernel activation heuristic explained in Sect. 3.1. To find the optimal parameters, we apply CMA-ES (Hansen 2006) where we use the negative log-likelihood of the ground-truth to the smoothed estimate as ...
This preference may be explained by the fact that an RBF kernel produces smooth functions and cannot capture non-differentiable points, such as the triangle’s vertex. To test this hypothesis, we derived an additional simulation setting where the conditional expectation is quadratic and U-shaped. ...
B73 kernels typically have a dented, collapsed starchy crown, with most of the hard, vitreous endosperm located on the abgerminal kernel side. In contrast, the top offka1-1kernels is convex and vitreous endosperm forms on both the abgerminal and adgerminal sides of the kernel (Fig.1b). W...
are natural basis functions of Xj1 and Xj2 respectively and X~j1j2=g1(Xj1)q1(Xj2) the basis expansion of the interaction between Xj1 and Xj2, as explained in [34]. The complete model formulation makes the following assumptions for the response Yi for individual i, i:1…n, n the ...
The integration of QTL mapping and genome-wide association analysis (GWAS) identified two SNPs, 8_166371888 and 8_178656036, which overlapped the QTL interval ofqSC8-1, identified in the tropical maize line YML46. The phenotypic variance explained (PVE) by the QTLqSC8-1was12.17%, while the...
Using this covariance structure, it was inferred that the correlation between the measurements at any two locations x and x⁎ will decay as the spatial separation between them increases as was also explained previously in the premise of the model. Thus, a multi-variate Gaussian distribution can...
That explained the fairly good performance of Wilcoxon test presented in Figure 2. Figure 1 Histogram of p-values. Histogram of p-values on the simulated data with low group effect, 20% missing data and 50% differentially expressed metabolites. The titles (a), (b), (c), (d), (e),...
Small deviations in the separation can be explained by the process described in Section 3.4. This process includes applying a regularization term (\(\lambda Id\)), utilizing a train-test-split, and incorporating additional randomness, which could explain any variance in the separation. Similar to...
the loss landscape remains convex when the model is trained and the optimal model with respect to this estimated Gram matrix is guaranteed to be obtained. Although this trained model is independent of input data (as explained above), the model can still perform well on the training phase and ...