Regions with a high prevalence of cases are extracted by means of binary classifiers, then the most relevant variables for the classification are determined, and the robustness of the analysis is assessed. Our results show that the most meaningful features to identify high-prevalence regions include...
Thus the observation leads to multi- ple hypotheses that are related to the generalization behav- iors of CNN, including a potential explanation for adver- sarial examples, a discussion of CNN's trade-off between robustness and accuracy, and some...
Our approach thus provides new avenues to reduce the complexity of quantifying ecosystem function and to increase model robustness (Prentice et al., 2015) by focusing on Π groups that embed ecologically meaningful mechanisms instead of individual parameters. 4.2. Ecohydrological optimality explains plant...
Min-protein oscillations in Escherichia coli are characterized by the remarkable robustness with which spatial patterns dynamically adapt to variations of cell geometry. Moreover, adaption, and therefore proper cell division, is independent of temperature. These observations raise fundamental questions about...
This subset of features can be analyzed together with metrics of the performance of the algorithms (such as the final quality of the solutions, the execution time, the number of iterations, and robustness) to obtain relationships that explain the process behavior. To achieve this objective, cause...
This subset of features can be analyzed together with metrics of the performance of the algorithms (such as the final quality of the solutions, the execution time, the number of iterations, and robustness) to obtain relationships that explain the process behavior. To achieve this objective, cause...