Abstract: Bayesian Network is a significant graphical model that is used to do probabilistic inference and reasoning under uncertainty circumstances. In many applications, existence of discrete and ...

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This repository implements a method to estimate a density-ratio. It is largely based on https://github.com/ermongroup/dre-infinity/. We have cleaned up the code a bit ...

This important study of artificial selection in microbial communities shows that the possibility of selecting a desired fraction of slow and fast-growing types is impacted by their initial fractions.

Operational streamflow forecasting is an effective non-structural measure to contain flood risk and protect human lives. Starting from weather models, which prognosticate future precipitation to drive ...

What Is A Probability Density Function? A probability density function, also known as a bell curve, is a fundamental statistics concept, that describes the likelihood of a continuous random variable ...

In real-world applications, datasets frequently contain outliers, which can hinder the generalization ability of machine learning models. Bayesian classifiers, a popular supervised learning method, ...

ABSTRACT: The evolution of ASE noise and the generation of nonlinear phase shift are analyzed based on the travelling wave solution of ASE noise and its probability density function by solving the ...