Comparison and remindings are both important cognitive processes that allow us to generalize across similar instances and generate new, abstracted knowledge.
GPR is built on Gaussian process, which is a stochastic process that generalizes multivariate Gaussian distribution to infinite-dimensional space such that distributions over function values can be defined.
In this article, we present a method to transform nonlinear primal models of pathways or other biotechnological processes that conform to the Generalized Mass Action (GMA) structure within the formalism of Biochemical Systems Theory (BST) into dual models that focus on fluxes, rather than pools.
Accordingly, Stanley generalizes contextual saturation processes that are usually regarded as characteristic of indexicals, tense, and a few other structures; moreover, he requires that the relevant variables be linguistically encoded, either syntactically or lexically.
They are generally built using a bottom up approach that generalizes small-physics representations of processes.
Here, distributions proposed by Sarmanov (1966) and Olkin & Liu (2003) are discussed and generalized as candidate processes that could be used to model this type of association.
Current anonymization algorithms aim to improve data privacy by generalizing the Q-ID attributes through processes that utilize taxonomy tree, interval, or suppression.
The aim of this qualitative study was, however, not to generalize the results, but rather to increase our understanding of processes that were hardly studied before.
This model describes movement planning as a continuous process on the basis of visual information pertaining to the free-kick trajectory, in a manner that generalizes to all forms of interception [16], [23], [24].
If episodic memory were the only process involved, we would expect to find a unique neural representation for each combination of location and direction and would not find evidence for direction coding that generalizes across locations.
