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According to them "regarding all possible developments that may be relevant for a problem, each development has an infinitesimal probability of coming true".
Furthermore, when regarding all possible developments that may be relevant for a problem, each development only has an infinitesimal probability of coming true.
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Since the available information on the input is usually incomplete, it is rarely possible to find uniquely the output properties relevant for a stochastic problem.
Frequently, it has been observed that certain descriptors appear to be relevant for a specific problem (for example, the molecular weight of a drug is an important parameter that may affect the capacity of a drug to permeate across the blood-brain barrier [17]).
We have presented a new method for lumping peripheral 1D model vessels into 0D windkessel models that enables us to analyze the effect of network topology on pulse waveforms and determine the optimal number of arterial segments (and hence input parameters) required to simulate efficiently blood pressure and flow waveforms at the arterial sites that are relevant for a particular problem.
IDENTIFYING the degree of admixture in individuals and inferring the population of origin of specific loci in these individuals is relevant for a variety of problems in population genetics.
But there is of course also the problem of relevance: what aspects are relevant for the problem at hand; which properties do we need to take into consideration?
The CPS frameworks developed explicate a number of skills relevant for collaborative problem solving, pulling from literature across many research areas, such as computer-supported collaborative learning, individual problem solving, and team discourse analysis.
This high throughput performance qualifies the presented methods to perform screenings on large databases with the aim to select relevant subsets for a given problem.
Besides the particular penalty function investigated in this article, we believe our results support the general idea that engineering relevant priors for a particular problem can have important effects on the quality of the function estimated and paves the way for further research on the engineering of such priors in combination with large-margin classifiers.
Similarly to what has been done to rationalize the determinants of protein aggregation (Chiti et al., 2003), the cleverSuite identifies the most relevant properties for a specific problem with the main differences being that: (i) fitting parameters are avoided and (ii) features are selected from a large pool of physico-chemical characteristics.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com