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We propose a novel algorithm based on inexact GMRES methods for linear response calculations in density functional theory. Such calculations require iteratively solving a nested linear problem $\mathcal{E} \delta\rho = b$ to obtain the…

Numerical Analysis · Mathematics 2025-10-30 Michael F. Herbst , Bonan Sun

We describe the numerical scheme for the discretization and solution of 2D elliptic equations with strongly varying piecewise constant coefficients arising in the stochastic homogenization of multiscale composite materials. An efficient…

Numerical Analysis · Mathematics 2019-04-01 Venera Khoromskaia , Boris N. Khoromskij , Felix Otto

We show that DBSCAN can estimate the connected components of the $\lambda$-density level set $\{ x : f(x) \ge \lambda\}$ given $n$ i.i.d. samples from an unknown density $f$. We characterize the regularity of the level set boundaries using…

Machine Learning · Statistics 2017-07-24 Heinrich Jiang

Minimum Variance Distortionless Response (MVDR) is a classical adaptive beamformer that theoretically ensures the distortionless transmission of signals in the target direction, which makes it popular in real applications. Its noise…

Sound · Computer Science 2024-09-16 Jinglin Bai , Hao Li , Xueliang Zhang , Fei Chen

We present a novel coarse-to-fine framework that derives a semi-regular multiscale mesh representation of an original input mesh via remeshing. Our approach differs from the conventional mesh wavelet transform strategy in two ways. First,…

Image and Video Processing · Electrical Eng. & Systems 2018-10-09 Hao-Chiang Shao

We develop a new, efficient, and accurate method to simulate frequency-domain borehole electromagnetic (EM) measurements acquired in the presence of three-dimensional (3D) variations of the anisotropic subsurface conductivity. The method is…

Real-time density estimation is ubiquitous in many applications, including computer vision and signal processing. Kernel density estimation is arguably one of the most commonly used density estimation techniques, and the use of "sliding…

Machine Learning · Statistics 2023-11-13 Yinsong Wang , Yu Ding , Shahin Shahrampour

Effectively continuous control over propagation of a beam of light requires light modulation with pixelation that is smaller than the optical wavelength. Here we propose a spatial intensity modulator with sub-wavelength resolution in one…

Optics · Physics 2016-11-21 Pablo Cencillo-Abad , Nikolay I. Zheludev , Eric Plum

Given any domain $X\subseteq \mathbb{R}^d$ and a probability measure $\rho$ on $X$, we study the problem of approximating in $L^2(X,\rho)$ a given function $u:X\to\mathbb{R}$, using its noiseless pointwise evaluations at random samples. For…

Numerical Analysis · Mathematics 2019-07-11 Giovanni Migliorati

In numerous applications data are observed at random times and an estimated graph of the spectral density may be relevant for characterizing and explaining phenomena. By using a wavelet analysis, one derives a nonparametric estimator of the…

Statistics Theory · Mathematics 2009-11-27 Jean-Marc Bardet , Pierre Bertrand

The numerical analysis of elastic wave propagation in unbounded media may be difficult to handle due to spurious waves reflected at the model artificial boundaries. Several sophisticated techniques such as nonreflecting boundary conditions,…

Classical Physics · Physics 2010-09-06 Jean-François Semblat , Ali Gandomzadeh , Luca Lenti

We propose a new wavelet-based method for density estimation when the data are size-biased. More specifically, we consider a power of the density of interest, where this power exceeds 1/2. Warped wavelet bases are employed, where warping is…

Methodology · Statistics 2022-12-08 Michel H. Montoril , Aluísio Pinheiro , Brani Vidakovic

Recent studies have shown that 2D convolution and self-attention exhibit distinct spectral behaviors, and optimizing their spectral properties can enhance vision model performance. However, theoretical analyses remain limited in explaining…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Guhnoo Yun , Juhan Yoo , Kijung Kim , Jeongho Lee , Paul Hongsuck Seo , Dong Hwan Kim

Imaging an object embedded within a scattering medium requires the correction of complex sample-induced wave distortions. Existing approaches have been designed to resolve them by optimizing signal waves recorded in each 2D image. Here, we…

Optics · Physics 2022-10-17 Ye-Ryoung Lee , Dong-Young Kim , Yonghyeon Jo , Moonseok Kim , Wonshik Choi

Segmentation, a useful/powerful technique in pattern recognition, is the process of identifying object outlines within images. There are a number of efficient algorithms for segmentation in Euclidean space that depend on the variational…

Computer Vision and Pattern Recognition · Computer Science 2019-11-12 Xiaohao Cai , Christopher G. R. Wallis , Jennifer Y. H. Chan , Jason D. McEwen

We construct a structure preserving non-conforming finite element approximation scheme for the bi-harmonic wave maps into spheres equation. It satisfies a discrete energy law and preserves the non-convex sphere constraint of the continuous…

Numerical Analysis · Mathematics 2026-04-09 Ľubomír Baňas , Sebastian Herr

Let $(X_i)_{i\geq 1}$ be an i.i.d. sample on $\RRR^d$ having density $f$. Given a real function $\phi$ on $\RRR^d$ with finite variation and given an integer valued sequence $(j_n)$, let $\fn$ denote the estimator of $f$ by wavelet…

Statistics Theory · Mathematics 2012-01-27 Davit Varron

In this short note, we compute the conformal stereographic projection on the standard metric of a sphere quotient. The result is a Majumdar-Papapetrou metric, which might be useful.

Differential Geometry · Mathematics 2023-04-18 Gautier Dietrich

A recently developed new approach, called ``Empirical Wavelet Transform'', aims to build 1D adaptive wavelet frames accordingly to the analyzed signal. In this paper, we present several extensions of this approach to 2D signals (images). We…

Functional Analysis · Mathematics 2024-11-01 Jerome Gilles , Giang Tran , Stanley Osher

We formulate an optimization problem to estimate probability densities in the context of multidimensional problems that are sampled with uneven probability. It considers detector sensitivity as an heterogeneous density and takes advantage…

Machine Learning · Computer Science 2025-06-04 Aleix Boquet-Pujadas , Pol del Aguila Pla , Michael Unser
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