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We consider the wave equation with highly oscillatory initial data, where there is uncertainty in the wave speed, initial phase and/or initial amplitude. To estimate quantities of interest related to the solution and their statistics, we…

Numerical Analysis · Mathematics 2015-09-11 Gabriela Malenova , Mohammad Motamed , Olof Runborg , Raul Tempone

We survey many of the important properties of spherically symmetric spacetimes as follows. We present several different ways of describing a spherically symmetric spacetime and the resulting metrics. We then focus our discussion on an…

General Relativity and Quantum Cosmology · Physics 2014-10-10 Alan R. Parry

We establish a general form of explicit, input-dependent, measure-valued warpings for learning nonstationary kernels. While stationary kernels are ubiquitous and simple to use, they struggle to adapt to functions that vary in smoothness…

Machine Learning · Computer Science 2020-10-12 Anthony Tompkins , Rafael Oliveira , Fabio Ramos

Purpose: Field monitoring using field probes allows for accurate measurement of magnetic field perturbations, such as from eddy currents, during MRI scanning. However, errors may result when the spatial variation of the fields is not…

Seismic attributes calculated by conventional methods are susceptible to noise. Conventional filtering reduces the noise in the cost of losing the spectral bandwidth. The challenge of having a high-resolution and robust signal processing…

Geophysics · Physics 2020-12-02 M. Kazemnia Kakhki , W. J. Mansur , K. Aghazadeh

Compared with the traditional spherical harmonics, the spherical needlets are a new generation of spherical wavelets that possess several attractive properties. Their double localization in both spatial and frequency domains empowers them…

Methodology · Statistics 2015-08-25 Minjie Fan

In recent years more and more long-term broadband data sets are collected in geosciences. Therefore there is an urgent need of algorithms which semi-automatically analyse and decompose these data into separate periods which are associated…

Geophysics · Physics 2015-05-30 Matthias Ehrhardt , Heiner Villinger , Stefan Schiffler

Spatial variables can be observed in many different forms, such as regularly sampled random fields (lattice data), point processes, and randomly sampled spatial processes. Joint analysis of such collections of observations is clearly…

Methodology · Statistics 2026-05-20 Jake P. Grainger , Tuomas A. Rajala , David J. Murrell , Sofia C. Olhede

In this pedagogically motivated work, the process of migration in reflection seismics has been considered from a rigorously mathematical viewpoint. An inclined subsurface reflector with a constant dipping angle has been shown to cause a…

Geophysics · Physics 2008-10-16 Arnab K. Ray

We propose a new shape analysis approach based on the non-local analysis of local shape variations. Our method relies on a novel description of shape variations, called Local Probing Field (LPF), which describes how a local probing operator…

Computational Geometry · Computer Science 2017-11-03 Julie Digne , Sébastien Valette , Raphaëlle Chaine

Approximation/interpolation from spaces of positive definite or conditionally positive definite kernels is an increasingly popular tool for the analysis and synthesis of scattered data, and is central to many meshless methods. For a set of…

Numerical Analysis · Mathematics 2013-09-11 E. Fuselier , T. Hangelbroek , F. J. Narcowich , J. D. Ward , G. B. Wright

Energy dissipation is highly intermittent in turbulent plasmas, being localized in coherent structures such as current sheets. The statistical analysis of spatial dissipative structures is an effective approach to studying turbulence. In…

High Energy Astrophysical Phenomena · Physics 2015-09-16 Vladimir Zhdankin , Dmitri A. Uzdensky , Stanislav Boldyrev

Seismology was developed on Earth and shaped our model of the Earth's interior over the 20th century. With the exception of the Philae lander, all in situ extraterrestrial seismological effort to date was limited to other terrestrial…

This paper describes an interdisciplinary approach to geometry modeling of geospatial boundaries. The objective is to extract surfaces from irregular spatial patterns using differential geometry and obtain coherent directional predictions…

Computational Engineering, Finance, and Science · Computer Science 2020-06-09 Raymond Leung

Quantifying spatial and/or temporal associations in multivariate geolocated data of different types is achievable via spatial random effects in a Bayesian hierarchical model, but severe computational bottlenecks arise when spatial…

Methodology · Statistics 2024-04-02 Michele Peruzzi , David B. Dunson

Spatial models are used in a variety research areas, such as environmental sciences, epidemiology, or physics. A common phenomenon in many spatial regression models is spatial confounding. This phenomenon takes place when spatially indexed…

Methodology · Statistics 2021-06-08 Isa Marques , Thomas Kneib , Nadja Klein

Modern seismic and volcanic monitoring is increasingly shaped by continuous, multi-sensor observations and by the need to extract actionable information from nonstationary, noisy wavefields. In this context, machine learning has moved from…

Machine Learning · Computer Science 2026-03-19 William Thorossian

A recent theoretical breakthrough has brought a new tool, called \emph{localization landscape}, to predict the localization regions of vibration modes in complex or disordered systems. Here, we report on the first experiment which measures…

Since the early 1960s, the fields of signal processing, data transmission, channel equalisation, filter design and others have been technologically developed and modernised as a result of the research carried out by D. Slepian and his…

Functional Analysis · Mathematics 2024-05-24 Boulsane Mourad

Graph Signal Processing generalizes classical signal processing to signal or data indexed by the vertices of a weighted graph. So far, the research efforts have been focused on static graph signals. However numerous applications involve…

Machine Learning · Computer Science 2016-06-22 Francesco Grassi , Nathanael Perraudin , Benjamin Ricaud
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