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Through a cascade of generalizations, we develop a theory of motivic integration which works uniformly in all non-archimedean local fields of characteristic zero, overcoming some of the difficulties related to ramification and small residue…

Logic · Mathematics 2017-03-14 Raf Cluckers , Immanuel Halupczok

We optimize a numerical time-stabilization routine for the phase-field crystal (PFC) models of solidification. By numerical experiments, we showcase that our approach can improve the accuracy of underlying time integration schemes by a few…

Materials Science · Physics 2023-07-06 Maik Punke , Steven M. Wise , Axel Voigt , Marco Salvalaglio

Finite-temperature effects can be included by calculating the vibrations properties and this can greatly improve the fidelity of computational screening. An important challenge for DFT-based screening is the sensitivity of the predictions…

Materials Science · Physics 2020-07-07 Pinwen Guan , Gregory Houchins , Venkatasubramanian Viswanathan

We give polynomial-time algorithms for the exact computation of lowest-energy (ground) states, worst margin violators, log partition functions, and marginal edge probabilities in certain binary undirected graphical models. Our approach…

Machine Learning · Computer Science 2009-09-29 Nicol N. Schraudolph , Dmitry Kamenetsky

The density estimation is one of the core problems in statistics. Despite this, existing techniques like maximum likelihood estimation are computationally inefficient due to the intractability of the normalizing constant. For this reason an…

Machine Learning · Computer Science 2021-01-14 Tsimboy Olga , Yermek Kapushev , Evgeny Burnaev , Ivan Oseledets

Code verification plays an important role in establishing the credibility of computational simulations by assessing the correctness of the implementation of the underlying numerical methods. In computational electromagnetics, the numerical…

Computational Physics · Physics 2023-06-05 Brian A. Freno , Neil R. Matula

The intrinsic mode function (IMF) provides adaptive function bases for nonlinear and non-stationary time series data. A fast convergent iterative method is introduced in this paper to find the IMF components of the data, the method is…

Numerical Analysis · Computer Science 2008-09-11 Louis Yu Lu

The study of the moments of the partially transposed density matrix provides a new and effective way of detecting bipartite entanglement in a many-body mixed state. This is valuable for cold-atom and ion-trap experiments, as well as in the…

Statistical Mechanics · Physics 2022-10-04 Sara Murciano , Vincenzo Alba , Pasquale Calabrese

We study theoretical limits of \emph{descending} phase retrieval algorithms. Utilizing \emph{Random duality theory} (RDT) we develop a generic program that allows statistical characterization of various algorithmic performance metrics.…

Machine Learning · Statistics 2025-06-24 Mihailo Stojnic

A general framework with a series of different methods is proposed to improve the estimate of convex function (or functional) values when only noisy observations of the true input are available. Technically, our methods catch the bias…

Methodology · Statistics 2022-09-15 Chao Ma , Lexing Ying

Deconvolution is a statistical inverse problem to estimate the distribution of a random variable based on its noisy observations. Despite the extensive studies on the topic, deconvolution with unknown noise distribution remains as a…

Statistics Theory · Mathematics 2020-04-06 Devavrat Shah , Dogyoon Song

We present a fast and accurate algorithm for the evaluation of nonlocal (long-range) Coulomb and dipole-dipole interactions in free space. The governing potential is simply the convolution of an interaction kernel $U(\bx)$ and a density…

Numerical Analysis · Mathematics 2014-10-07 Shidong Jiang , Leslie Greengard , Weizhu Bao

A recent development in the theory of fractional differential equations with variable coefficients has been a method for obtaining an exact solution in the form of an infinite series involving nested fractional integral operators. This…

Classical Analysis and ODEs · Mathematics 2021-05-04 Arran Fernandez , Joel E. Restrepo , Durvudkhan Suragan

The convergence to the self-consistency in the dynamical-mean-field-theory (DMFT) calculations for models of correlated electron systems can be significantly accelerated by using an appropriate mixing of hybridization functions which are…

Strongly Correlated Electrons · Physics 2009-11-11 Rok Zitko

Conventional wavelet-domain methods for room impulse response denoising rely on thresholding detail coefficients, which is unsuited for low frequencies. In this work, we introduce a wavelet-based post-processing algorithm that extends…

Sound · Computer Science 2026-04-30 Théophile Dupré , Romain Couderc , Miguel Moleron , Axel Coulon , Rémy Bruno , Arnaud Laborie

Deploying deep learning models on embedded systems has been challenging due to limited computing resources. The majority of existing work focuses on accelerating image classification, while other fundamental vision problems, such as object…

Computer Vision and Pattern Recognition · Computer Science 2021-01-27 Zhen Dong , Dequan Wang , Qijing Huang , Yizhao Gao , Yaohui Cai , Tian Li , Bichen Wu , Kurt Keutzer , John Wawrzynek

Adaptive Local Iterative Filtering (ALIF) is a currently proposed novel time-frequency analysis tool. It has been empirically shown that ALIF is able to separate components and overcome the mode-mixing problem. However, so far its…

Numerical Analysis · Mathematics 2020-05-12 Antonio Cicone , Hau-Tieng Wu

We present the results of a National Science Foundation (NSF) Project Scoping Workshop, the purpose of which was to assess the current status of calculations for the nuclear matrix elements governing neutrinoless double-beta decay and…

This paper presents a class of Crank-Nicolson (CN) type schemes enhanced by radial basis function (RBF) interpolation for the time integration of linear parabolic partial differential equations (PDEs). The resulting RBF-CN schemes preserve…

Numerical Analysis · Mathematics 2025-09-09 Subhankar Nandi , Satyajit Pramanik

The research paper addresses linear decomposition of time series of non-additive metrics that allows for the identification and interpretation of contributing factors (input features) of variance. Non-additive metrics, such as ratios, are…

Machine Learning · Computer Science 2022-04-15 Alex Glushkovsky
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