Sentence examples for based on graphical models from inspiring English sources

Numerous latent topic-based image retrieval frameworks are available in the literature, and the majority of these approaches are based on graphical models.

Approaches based on graphical models try to maximize the joint distribution of visual words and the latent topics to effectively capture the latent topic structures present in the visual word collection.

This work aims to provide empirical evidence of such advantages by comparing recursive modeling method from LCFs and collaborative design network from TCFs, both of which are decision-theoretic and the latter of which is based on graphical models.

In recent years, Bayesian Networks (BNs) have become a popular representation based on graphical models for modelling stochastic processes with consideration of uncertainty in various fields, from computational biology to complex engineering problems.

Such analysis, based on graphical models, explicitly incorporates the dependence structure among genes highlighted by the topology of pathways.

The geometric and kinematic design of the robot was performed based on graphical modeling and simulation through interference analysis and visualization.

In order to achieve better performance, this work aims to design a novel neural network architecture called Inference Embedded Deep Networks (IEDNs), which incorporates a novel designed inference layer based on graphical model.

In addition, based on Graphical model, given y, the conditional distributions of different algorithms are independent, such as p x1| s1, y) is conditional independent of p x2| s2, y).

Finally, we compared GENIE3 to three existing approaches based on the computation of mutual information (MI), namely CLR [11], ARACNE [12] and MRNET [14], and to one approach based on graphical Gaussian models (GGMs) [20].

Here we shall follow this latter approach, and add a stochastic framework, based on graphical Gaussian models.

Here we describe a novel approach for quantifying the differences in gene-gene connectivity patterns across disease states based on Graphical Gaussian Models (GGMs).