Sentence examples for using probabilistic models to from inspiring English sources

By using probabilistic models to predict each avatar's future motion and the virtual region its area of interest (AOI) will cover, a density-based method is proposed to help each server construct avatar clusters from its local avatars in parallel.

More sophisticated risk assessment methods, using probabilistic models to study variability in pesticide residue levels and food consumption data, would be needed to achieve this task.

Drawbridge's main feat is to use probabilistic models to try to infer whether a desktop user and a mobile user are the same person.

Its platform uses probabilistic models "to generalise to novel situations and adapt to changing environments by refining their strategies in data-driven ways"; Reinforcement Learning algorithms that estimate and account for uncertainty; and Game Theory to operate in multi-agent settings to infer what humans and other AIs are trying to do.

Its platform uses probabilistic models "to generalise to novel situations and adapt to changing environments by refining their strategies in data-driven ways"; Reinforcement Learning algorithms that estimate and account for uncertainty; and Game Theory to operate in multi-agent settings to infer what humans and other AIs are trying to do.

The FluSurv-NET disease burden model uses probabilistic models to account for age-specific influenza testing practices and case underreporting and extrapolates data from FluSurv-NET sites to arrive at national estimates.

A significant amount of recent work in CATs for assisting people with cognitive impairments use probabilistic models to infer task and occupant status from sensors distributed throughout a person's living environment [ 11].

One recent example that utilizes prior knowledge is the PARADIGM approach (Vaske et al., 2010) which uses probabilistic models to integrate genetics, epigenetics and transcriptional data with curated pathway information to determine active pathways in cancer patients, but does not directly attempt a prediction of response and non-response status in trial data.

InterVA-4 uses probabilistic modelling to arrive at likely cause(s) of death for each VA case, the workings of the model being based on a combination of expert medical opinion and relevant available data.

Another approach was taken by Vincent Daubin (Lyon University, France), who used probabilistic modeling to simultaneously reconstruct the species tree and the gene trees, as well as all the implied gene duplication, loss and transfer events (Boussau et al., 2012).

In [19-22] [19-22]s havexpertsidentified by using probabilistic models.