Sentence examples for probabilistic derivation from inspiring English sources
Though considered as an ansatz in the whole physics literature, it seems that it is the first rigorous probabilistic derivation of the semiclassical limit of LFT.
They have studied different properties of the DML distribution, gave a probabilistic derivation and an application in a first order autoregressive discrete process.
It is well known that the exponential inequality for the random variables is very useful in several probabilistic derivations.
As we know, the limiting behavior for the maximum of weighted sums (max_{1leq mleq n}sum_{i=1}^{m} b_{ni}X_{ni}) is very useful in many probabilistic derivations and stochastic models.
The derivation of probabilistic rules based on the transition probabilities between individual prototypes is the stringent extension of the presented approach for describing complex sequences (Geurten et. al. submitted).
This viewpoint highlights probabilistic assumptions underlying different derivations and serves as a basis for developing new algorithms for linear and nonlinear AEC and similar tasks.
Optimization-based and probabilistic approaches use mathematical derivations to determine best scoring modules.
In particular, the software program ProFatigue is used for derivation of the probabilistic S N field from experimental fatigue data.
The derivation of a probabilistic output from a classification-based model was introduced in Evans and Cushman ([27]) as an extension of the original Breiman ([26]) algorithm.
The derivation of a probabilistic functional network from functional genomics and proteomics data using the log-likelihood strategy is an example of a supervised learning approach, distinguishing positive functional associations from negative associations on the basis of the performance of training associations in the data sets under analysis.
This consistent Bayesian view on conceptually different algorithms highlights the probabilistic assumptions underlying the respective derivations and provides a powerful framework for further research in linear and nonlinear AEC.
