Contact mechanics examines the deformation and interaction of bodies at interfaces where separation, adhesion and friction may occur. Variational methods reformulate contact problems as inequalities ...

Industry groups and drugmakers want the US Food and Drug Administration (FDA) to explicitly clarify that Bayesian statistical methods can be used for products beyond those intended for children and ...

The last 25 years have seen significant advances in the modeling and mathematical analysis of fracture. However, the strongest mathematical results have been restricted to variational models that have ...

ABSTRACT: In this paper, we are concerned with the following nonlocal Schrödinger equations − ℒ K u+V( x )u=f( x,u ), x∈ ℝ N , where − ℒ K is an integro-differential operator of fractional Laplacian ...

We introduce HVAC (Hierarchical Bayesian model with Variational inference and functional Annotation integration for Cross-ancestry prediction), a novel cross-population PRS framework employing a three ...

Generative Modeling is a branch of machine learning that focuses on creating models representing distributions of data, denoted as $P(X)$. $X$ represents the data ...

ABSTRACT: In this paper, we establish an SIR reaction-diffusion infectious disease model with saturated incidence rate and vaccination. Firstly, we prove the uniform boundedness of the solution of ...

In the intertwined worlds of psychology, cognitive neuroscience, and artificial intelligence, scientists continue to pursue the elusive goal of decoding and mimicking human and animal behavior. One of ...

Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...