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This work introduces probabilistic multiple hypothesis anchoring to create and maintain a semantically rich world model using probabilistic anchoring.
Uncertainty is addressed in the model using probabilistic sensitivity analysis.
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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.
The underlying uncertainty is modeled using probabilistic theory.
Listing 3 shows an example where uncertainty is modeled using probabilistic and conditional rules.
In this paper, we advocate the use of the uncompressed form of i-vector and depend on subspace modeling using probabilistic linear discriminant analysis (PLDA) in handling the speaker and session (or channel) variability.
Scenario modelling using probabilistic data derived from the UKCP09 weather generator (WG) in conjunction with dynamic simulation and global sensitivity analysis techniques are used to assess the future performance of a range of typical Passivhaus dwellings relative to an identical Fabric Energy Efficiency Standard FEESS) compliant dwelling over its notional future lifespan.
We will describe how the pump mechanism can be modeled using probabilistic model checking taking into consideration a discrete chemistry approach and the Law of Mass Action aspects.
For this, we use "ideal observer" models that link subjective distributions to behavior, and by inverting these models using probabilistic machine learning methods [ 20] we estimate the subjective distribution.
Very recently, more advanced models use probabilistic approaches [49] that consider dynamic input rates, in-use stocks as well as the continuous rise in production volumes [22].
The authors made use of the junction tree algorithm to model interference using probabilistic models obtained from the BNs.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com