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We investigate a quintessence model involving two scalar fields with double-exponential potentials. This configuration allows the system as a whole to emulate the dynamics of a single field with a shallower potential, enabling scalar fields…

Cosmology and Nongalactic Astrophysics · Physics 2025-10-27 George Alestas , Marienza Caldarola , Indira Ocampo , Savvas Nesseris , Shinji Tsujikawa

The Scanning electron microscope (SEM) and Electron-Dispersive Spectroscope (EDS) are two highly effective instruments in the field of nanoscience and nanotechnology. The quality of these instruments is determined by various factors, with…

Applied Physics · Physics 2023-10-24 Hamidreza Moradi , Fatemeh Mehradnia

This article proposes an efficient Bayesian inference for piecewise exponential hazard (PEH) models, which allow the effect of a covariate on the survival time to vary over time. The proposed inference methodology is based on a particle…

Computation · Statistics 2020-04-01 Parfait Munezero

Deep eutectic solvents (DESs) have gained attention in recent years as attractive alternatives to traditional solvents. There is a growing number of publications dealing with the thermodynamic modeling of DESs highlighting the importance of…

This work aims at making a comprehensive contribution in the general area of parametric inference for discretely observed diffusion processes. Established approaches for likelihood-based estimation invoke a time-discretisation scheme for…

Methodology · Statistics 2024-01-30 Yuga Iguchi , Alexandros Beskos , Matthew M. Graham

Two-dimensional electronic spectroscopy (2DES) has enabled significant discoveries in both biological and synthetic energy-transducing systems. Although deriving chemical information from 2DES is a complex task, machine learning (ML) offers…

Chemical Physics · Physics 2025-03-21 Jonathan D. Schultz , Kelsey A. Parker , Bashir Sbaiti , David N. Beratan

This paper concerns a spectral estimation problem in which we want to find a spectral density function that is consistent with estimated second-order statistics. It is an inverse problem admitting multiple solutions, and selection of a…

Optimization and Control · Mathematics 2019-08-08 Bin Zhu

Discontinuity preserving smoothing is a fundamentally important procedure that is useful in a wide variety of image processing contexts. It is directly useful for noise reduction, and frequently used as an intermediate step in higher level…

Computer Vision and Pattern Recognition · Computer Science 2011-03-31 Stuart B. Heinrich , Wesley E. Snyder

Exponential smoothers are a simple and memory efficient way to compute running averages of time series. Here we define and describe practical properties of exponential smoothers for signals observed at constant and variable intervals.

Machine Learning · Statistics 2015-02-13 Javier R. Movellan

Density functional theory (DFT) codes are commonly treated as a "black box" in high-throughput screening of materials, with users opting for the default values of the input parameters. Often, non-experts may not sufficiently consider the…

Materials Science · Physics 2021-09-08 Jeremy J. Jorgensen , Gus L. W. Hart

A prevalent problem in general state space models is the approximation of the smoothing distribution of a state conditional on the observations from the past, the present, and the future. The aim of this paper is to provide a rigorous…

Statistics Theory · Mathematics 2016-05-30 Thi Ngoc Minh Nguyen , Sylvain Le Corff , Eric Moulines

We present general analytical criteria for the design of lossless reciprocal two-port systems, which exhibit prescribed scattering spectra $S(\omega)$ satisfying $S_{22}(\omega)=e^{i\varphi}S_{11}(\omega)$, including symmetric…

Applied Physics · Physics 2022-03-17 Mohammed Benzaouia , John D. Joannopoulos , Steven G. Johnson , Aristeidis Karalis

The spectral density function describes the second-order properties of a stationary stochastic process on $\mathbb{R}^d$. This paper considers the nonparametric estimation of the spectral density of a continuous-time stochastic process…

Statistics Theory · Mathematics 2023-02-07 Rafail Kartsioukas , Stilian Stoev , Tailen Hsing

Expressive evaluation metrics are indispensable for informative experiments in all areas, and while several metrics are established in some areas, in others, such as feature selection, only indirect or otherwise limited evaluation metrics…

Machine Learning · Computer Science 2025-01-17 Muhammad Rajabinasab , Anton D. Lautrup , Tobias Hyrup , Arthur Zimek

Testing procedures for assessing specific parametric model forms, or for checking the plausibility of simplifying assumptions, play a central role in the mathematical treatment of the uncertain. No certain answers are obtained by testing…

We introduce a methodology for online estimation of smoothing expectations for a class of additive functionals, in the context of a rich family of diffusion processes (that may include jumps) -- observed at discrete-time instances. We…

Computation · Statistics 2022-07-04 Shouto Yonekura , Alexandros Beskos

We address the problem of parameter estimation for degenerate diffusion processes defined via the solution of Stochastic Differential Equations (SDEs) with diffusion matrix that is not full-rank. For this class of hypo-elliptic diffusions…

Statistics Theory · Mathematics 2024-09-04 Yuga Iguchi , Alexandros Beskos

Purpose: Biophysical tissue models are increasingly used in the interpretation of diffusion MRI (dMRI) data, with the potential to provide specific biomarkers of brain microstructural changes. However, the general Standard Model has…

Biological Physics · Physics 2019-03-19 Santiago Coelho , Jose M. Pozo , Sune N. Jespersen , Derek K. Jones , Alejandro F. Frangi

The continuum approach employing porous media models is a robust and efficient solution method in the area of the simulation of fixed-bed reactors. This paper applies the double-averaging methodology to refine the continuum approach,…

Fluid Dynamics · Physics 2023-05-11 W. Sadowski , M. Sayyari , F. di Mare , H. Marschall

The joint bilateral filter, which enables feature-preserving signal smoothing according to the structural information from a guidance, has been applied for various tasks in geometry processing. Existing methods either rely on a static…

Graphics · Computer Science 2018-03-15 Juyong Zhang , Bailin Deng , Yang Hong , Yue Peng , Wenjie Qin , Ligang Liu