Artificial intelligence (AI) applied to abdominal imaging can help predict adults at higher risk of falling as early as ...

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

Through systematic experiments DeepSeek found the optimal balance between computation and memory with 75% of sparse model ...

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 ...

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

In this paper, we consider the function f p ( t )= 2p X 2 ( 2p t+p;p ) , where χ²(x; n) defined by X 2 ( x;p )= 2 −p/2 Γ( p/2 ) e −x/2 x p/2−1 , is the density function of a χ²-distribution with n ...

Abstract: The Vlasov-Maxwell equations describe the coupled evolution of collisionless plasma particle distribution function (PDF) and the electromagnetic field. The system is exceedingly multiscale ...

The Riemann hypothesis is the most important open question in number theory—if not all of mathematics. It has occupied experts for more than 160 years. And the problem appeared both in mathematician ...

Point process provides a mathematical framework for characterizing neuronal spiking activities. Classical point process methods often focus on the conditional intensity function, which describes the ...