The US Commerce Department's Bureau of Industry and Security (BIS) has shifted its license review policy for exports of ...

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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Bayesian statistics remain popular for addressing inverse problems, whereby quantities of interest are determined from their noisy and indirect observations. Bayes’ theorem forms the foundation of ...

This paper introduces MaCoDE, a method that reframes masked language modeling as conditional density estimation for generating synthetic tabular data. It achieves high machine learning utility, ...

We propose a new framework that addresses endogenous regressors using a novel conditional copula endogeneity model to capture the regressor-error dependence ...

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.