<p>The theoretical calculations is compared with the simulations for <i>f</i> = 0.2. Note that the capacity in the sparse regime is higher than in the dense regime.</p
<p>A–B. Dependence on coding levels. A. Maximal capacity as a function of for different coding leve...
<p>(A) The number of estimated nuclei and the scores of (B) precision, and (C) sensitivity, and (D) ...
<p>We show the average F-measure for each soft-margin parameter <i>C</i> in 1,000 optimal solutions....
(A) The storage capacity decreases when the noise strength increases strongly depends on r1. Small v...
<p><b>A.</b> The red plot shows the critical capacity as a function of the size of the basins of att...
<p>We varied the strength of the external field (<i>γ</i>) in order to quantify its effect on the le...
<p>As the robustness, we show the average F-measure in 1,000 optimal solutions. The types of perturb...
Orange squares represent the storage capacity for the model with the learning rule defined in Eq (6)...
<p>Both connection-removal and misexpression perturbations are applied to the estimated networks. As...
When C is small (e.g., C = 0, 1, 2, 3), the storage capacity p monotonically decreases with the nois...
The performance of the proposed model at two extreme thresholds with different sparsity.</p
<p>We show the average F-measure for each soft-margin parameter <i>C</i> in 1,000 optimal solutions....
International audienceWe study the capacity scaling of a system where a source communicates to a des...
<p>Robustness of all methods in situations of identical/different MAF distributions of signal and no...
(A) Dependence of p on C for . In the small r1 limit, the optimal potential width C* is zero (i.e., ...
<p>A–B. Dependence on coding levels. A. Maximal capacity as a function of for different coding leve...
<p>(A) The number of estimated nuclei and the scores of (B) precision, and (C) sensitivity, and (D) ...
<p>We show the average F-measure for each soft-margin parameter <i>C</i> in 1,000 optimal solutions....
(A) The storage capacity decreases when the noise strength increases strongly depends on r1. Small v...
<p><b>A.</b> The red plot shows the critical capacity as a function of the size of the basins of att...
<p>We varied the strength of the external field (<i>γ</i>) in order to quantify its effect on the le...
<p>As the robustness, we show the average F-measure in 1,000 optimal solutions. The types of perturb...
Orange squares represent the storage capacity for the model with the learning rule defined in Eq (6)...
<p>Both connection-removal and misexpression perturbations are applied to the estimated networks. As...
When C is small (e.g., C = 0, 1, 2, 3), the storage capacity p monotonically decreases with the nois...
The performance of the proposed model at two extreme thresholds with different sparsity.</p
<p>We show the average F-measure for each soft-margin parameter <i>C</i> in 1,000 optimal solutions....
International audienceWe study the capacity scaling of a system where a source communicates to a des...
<p>Robustness of all methods in situations of identical/different MAF distributions of signal and no...
(A) Dependence of p on C for . In the small r1 limit, the optimal potential width C* is zero (i.e., ...
<p>A–B. Dependence on coding levels. A. Maximal capacity as a function of for different coding leve...
<p>(A) The number of estimated nuclei and the scores of (B) precision, and (C) sensitivity, and (D) ...
<p>We show the average F-measure for each soft-margin parameter <i>C</i> in 1,000 optimal solutions....
DOI
Add to ORKG