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Figure 7 Graphical model for probabilistic backfitting.
Stochastic shortest path problem (SSP) [7] is another model for probabilistic planning.
This paper proposes a combination model for probabilistic short-term wind speed forecasting.
Markov Decision Processes have become the standard model for probabilistic planning.
Furthermore, the results emphasize the potential application of the model for probabilistic drought early warning in East Africa.
Their model includes node-to-node communication model of Wu and Varshney [3], multihop propagation of flooding modeled as a graph, and a model for probabilistic flooding.
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Graphical models are a suitable framework for probabilistic modelling.
Load effects are often discussed regarding modeling for probabilistic analyses.
The emergence of new sciences is aided by the development of new scientific tools, such as models for probabilistic reasoning, a kind of reasoning that gains new respect and application in the period.
We highlight design decisions and practical issues that must be addressed in order to use Gaussian process models for probabilistic prediction of a quantity of interest.
The models for probabilistic description of ontogenetic life-history transitions presented in this study are convenient in the sense that they can be readily fitted to an observed pattern of transition events without tight requirement of information of ontogenetic trajectories or temporal changes in covariates.
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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