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In biology experiments, oligonucleotide microarrays are contacted with a solution of long nucleic acid (NA) targets. The hybridized probes thus carry long tails. When the surface density of the oligonucleotide probes is high enough, the…
Nested error regression models are useful tools for analysis of grouped data, especially in the case of small area estimation. This paper suggests a nested error regression model using uncertain random effects in which the random effect in…
Using the predictive power of the effective field theory approach, we present a physical parametrization of the leading effects beyond the SM (BSM), that give us at present the best way to constrain heavy new-physics at low-energies. We…
Bayesian neural networks (BNNs) are a principled approach to modeling predictive uncertainties in deep learning, which are important in safety-critical applications. Since exact Bayesian inference over the weights in a BNN is intractable,…
The Stochastic Weighted Particle Method (SWPM) of Rjasanow and Wagner is a generalization of the Direct Simulation Monte Carlo method for computing the probability density function of the velocities of a system of interacting particles for…
A novel data-driven methodology is presented for the joint selection of prior parameters for both fixed and random effects in Linear Mixed Models (LMMs). This approach facilitates the estimation of complex random-effects structures, as well…
In this chapter we give an overview of the consensus-based global optimization algorithm and its recent variants. We recall the formulation and analytical results of the original model, then we discuss variants using component-wise…
Bayesian model mixing (BMM) is a statistical technique that can combine constraints from different regions of an input space in a principled way. Here we extend our BMM framework for the equation of state (EOS) of strongly interacting…
Low rank matrix approximation (LRMA) has drawn increasing attention in recent years, due to its wide range of applications in computer vision and machine learning. However, LRMA, achieved by nuclear norm minimization (NNM), tends to…
Coherent forward scattering processes by neutrino-scalar nonstandard interactions (SNSI) induce an effective neutrino mass. In the Early Universe, a large neutrino effective mass restricts the production of neutrinos. The SNSI effect is…
Within the framework of the MSSM, we compute the complete set of electroweak one-loop supersymmetric quantum effects on the width $\Gamma_Z$ of the $Z$-boson in the on-shell renormalization scheme. Numerical analyses of the corrections to…
To capture and simulate geometric surface evolutions, one effective approach is based on the phase field methods. Among them, it is important to design and analyze numerical approximations whose error bound depends on the inverse of the…
In the context of multicriteria decision making, the ordered weighted averaging (OWA) functions play a crucial role in aggregating multiple criteria evaluations into an overall assessment supporting the decision makers' choice. Determining…
We explore negative dependence and stochastic orderings, showing that if an integer-valued random variable $W$ satisfies a certain negative dependence assumption, then $W$ is smaller (in the convex sense) than a Poisson variable of equal…
Generalized neutrino interactions (GNI) are emerging as a convenient framework for describing effective scalar, vector, and tensor interactions. Such interactions arise naturally from extensions of the Standard Model that aim to explain…
We use a Bayesian regression technique (similar to a recent analysis by Rinaldi et al) to obtain a central estimate for the $W$-boson mass using four different combinations of datasets compiled by the PDG including the 2022 CDF result. We…
In forecasting problems it is important to know whether or not recent events represent a regime change (low long-term predictive potential), or rather a local manifestation of longer term effects (potentially higher predictive potential).…
The quality of HFB wave functions are tested by comparing the theoretically calculated results with the available experimental data for a number of spectroscopic properties like yrast spectra, reduced B(E2) transition probabilities,…
Wind-forced near-inertial waves (NIWs) propagate through a sea of mesoscale eddies, which can fundamentally alter their evolution. The nature of this NIW--mesoscale interaction depends on how dispersive the waves are. For weakly dispersive…
Recent measurements of the $pp\to t\bar{t}W^\pm$ process in multi-lepton final states, as performed by the ATLAS collaboration in the context of the Higgs boson studies in the $t\bar{t}H$ channel, have shown discrepancies between…