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In this paper, following the Backus (1962) approach, we examine expressions for elasticity parameters of a homogeneous generally anisotropic medium that is long-wave-equivalent to a stack of thin generally anisotropic layers. These…

Geophysics · Physics 2016-06-23 Len Bos , David R. Dalton , Michael A. Slawinski , Theodore Stanoev

Elastic anisotropy might be a combined effect of the intrinsic anisotropy and the anisotropy induced by thin-layering. The Backus average, a useful mathematical tool, allows us to describe such an effect quantitatively. The results are…

Geophysics · Physics 2021-01-08 Filip P. Adamus

We postulate that validity of the Backus (1962) average, whose weights are layer thicknesses, is limited to waves whose incidence is nearly vertical. The accuracy of this average decreases with the increase of the source-receiver offset.…

Geophysics · Physics 2020-11-11 David R. Dalton , Ayiaz Kaderali

In this paper, we continue the study of Bos et al. (2018) regarding statistical and numerical considerations of the Backus (1962) product approximation. While the approximation is typically quite good for seismological scenarios, Bos et al.…

Geophysics · Physics 2020-12-07 Ayiaz Kaderali , Izabela Kudela , Theodore Stanoev

We examine the Backus average of a stack of isotropic layers overlying an isotropic halfspace to examine its applicability for the quasi-Rayleigh and Love wave dispersion curves, both of which apply to the same model. We compare these…

Geophysics · Physics 2019-09-04 David R. Dalton , Thomas B. Meehan , Michael A. Slawinski

Backus (1962) developed his technique for homogenization of a layered structure solely within the context of linear elastic theory. In this paper we propose an extended use of Backus average for finitely deformed materials of a layered…

Classical Physics · Physics 2019-11-28 Andrey Melnikov

As shown by Backus (1962), the average of a stack of isotropic layers results in a transversely isotropic medium. Herein, we consider a stack of layers consisting of a randomly oriented anisotropic elasticity tensor, which-one might…

Geophysics · Physics 2018-04-20 Len Bos , Michael A. Slawinski , Theodore Stanoev

Continuous-time Bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact representation, inference in such models is intractable even…

Artificial Intelligence · Computer Science 2012-05-14 Ido Cohn , Tal El-Hay , Nir Friedman , Raz Kupferman

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

Statistics Theory · Mathematics 2009-04-03 Randal Douc , Aurelien Garivier , Eric Moulines , Jimmy Olsson

We consider the Bayesian detection statistic for a targeted search for continuous gravitational waves, known as the $\mathcal{B}$-statistic. This is a Bayes factor between signal and noise hypotheses, produced by marginalizing over the four…

General Relativity and Quantum Cosmology · Physics 2018-12-19 John J. Bero , John T. Whelan

In this paper, we derive an explicit upper bound for the Wasserstein distance between a functional of point processes and a Gaussian distribution. Using Stein's method in conjunction with Malliavin's calculus and the Poisson embedding…

Probability · Mathematics 2025-06-09 Laure Coutin , Benjamin Massat , Anthony Réveillac

Wave propagation in architectured materials, or materials with microstructure, is known to be dependent on the ratio between the wavelength and a characteristic size of the microstructure. Indeed, when this ratio decreases (i.e. when the…

Classical Physics · Physics 2017-07-24 Rosi Giuseppe , Placidi Luca , Auffray Nicolas

Standard sparse pseudo-input approximations to the Gaussian process (GP) cannot handle complex functions well. Sparse spectrum alternatives attempt to answer this but are known to over-fit. We suggest the use of variational inference for…

Machine Learning · Statistics 2015-03-23 Yarin Gal , Richard Turner

As a tool for capturing irregular temporal dependencies (rather than resorting to binning temporal observations to construct time series), Hawkes processes with exponential decay have seen widespread adoption across many application…

Machine Learning · Computer Science 2021-04-05 Tiago Santos , Florian Lemmerich , Denis Helic

Ordinary differential equations are arguably the most popular and useful mathematical tool for describing physical and biological processes in the real world. Often, these physical and biological processes are observed with errors, in which…

Methodology · Statistics 2016-07-26 Sarat C. Dass , Jaeyong Lee , Kyoungjae Lee , Jonghun Park

In this paper we show that the classical problem of frequency estimation can be formulated and solved efficiently in an empirical Bayesian framework by assigning a uniform a priori probability distribution to the unknown frequency. We…

Signal Processing · Electrical Eng. & Systems 2020-10-27 Giorgio Picci , Bin Zhu

We generalize the targeted $\mathcal{B}$-statistic for continuous gravitational waves by modeling the $h_0$-prior as a half-Gaussian distribution with scale parameter $H$. This approach retains analytic tractability for two of the four…

General Relativity and Quantum Cosmology · Physics 2026-02-27 Reinhard Prix

Hawkes process are very popular mathematical tools for modelling phenomena exhibiting a \textit{self-exciting} or \textit{self-correcting} behaviour. Typical examples are earthquakes occurrence, wild-fires, drought, capture-recapture, crime…

Computation · Statistics 2023-06-23 Francesco Serafini , Finn Lindgren , Mark Naylor

We consider a smooth forward facing step defined by the Gauss error function of height 4-30\% and four times the width of the local boundary layer thickness $\delta_{99}$. The boundary layer flow over a smooth forward-facing stepped plate…

Fluid Dynamics · Physics 2016-03-11 Hui Xu , Jean-Eloi W. Lombard , Spencer J. Sherwin

We consider a time-varying first-order autoregressive model with irregular innovations, where we assume that the coefficient function is H\"{o}lder continuous. To estimate this function, we use a quasi-maximum likelihood based approach. A…

Statistics Theory · Mathematics 2023-02-28 Hanna Gruber , Moritz Jirak
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