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The affine Grassmannian is a noncompact smooth manifold that parameterizes all affine subspaces of a fixed dimension. It is a natural generalization of Euclidean space, points being zero-dimensional affine subspaces. We will realize the…

Methodology · Statistics 2018-06-26 Lek-Heng Lim , Ken Sze-Wai Wong , Ke Ye

In this paper, we consider a modified projected Gauss-Newton method for solving constrained nonlinear least-squares problems. We assume that the functional constraints are smooth and the the other constraints are represented by a simple…

Optimization and Control · Mathematics 2025-04-02 Yassine Nabou , Lucian Toma , Ion Necoara

Koopman-based methods leverage a nonlinear lifting to enable linear regression techniques. Consequently, data generation, learning and prediction is performed through the lens of this lifting, giving rise to a nonlinear manifold that is…

Dynamical Systems · Mathematics 2025-06-24 Pieter van Goor , Robert Mahony , Manuel Schaller , Karl Worthmann

In this paper, we develop a robust efficient visual SLAM system that utilizes heterogeneous point and line features. By leveraging ORB-SLAM [1], the proposed system consists of stereo matching, frame tracking, local mapping, loop detection,…

Computer Vision and Pattern Recognition · Computer Science 2017-11-27 Xingxing Zuo , Xiaojia Xie , Yong Liu , Guoquan Huang

Two-dimensional free-surface flow over localised topography is examined with the emphasis on the stability of hydraulic-fall solutions. A Gaussian topography profile is assumed with a positive or negative amplitude modelling a bump or a…

Fluid Dynamics · Physics 2024-03-12 Jack S. Keeler , Mark G. Blyth

Physical realizations of the canonical phase measurement for the optical phase are unknown. Single-shot phase estimation, which aims to determine the phase of an optical field in a single shot, is critical in quantum information processing…

Quantum Physics · Physics 2022-08-16 M. A. Rodríguez-García , M. T. DiMario , P. Barberis-Blostein , F. E. Becerra

Calculations of electronic and optical properties of solids at finite temperature including electron-phonon interactions and quantum zero-point renormalization have enjoyed considerable progress during the past few years. Among the emerging…

Materials Science · Physics 2020-04-01 Marios Zacharias , Feliciano Giustino

We propose a Bayesian statistical model for analyzing coherent anti-Stokes Raman scattering (CARS) spectra. Our quantitative analysis includes statistical estimation of constituent line-shape parameters, underlying Raman signal,…

Applications · Statistics 2020-05-15 Teemu Härkönen , Lassi Roininen , Matthew T. Moores , Erik M. Vartiainen

Despite its numerical challenges, finite element method is used to compute viscous fluid flow. A consensus on the cause of numerical problems has been reached; however, general algorithms---allowing a robust and accurate simulation for any…

Computational Engineering, Finance, and Science · Computer Science 2019-02-05 Bilen Emek Abali

Here we present exact, stationary, parametric solutions to the Schr\"odinger--Poisson system. We confront two images: on one hand, we draw on the homotopy analysis method which leads us to a nonlinear integral scheme. Indeed, this approach…

Quantum Physics · Physics 2017-02-20 Jesús Fuentes , Pablo Galaviz , Tonatiuh Matos

We develop a fast method for computing the electrostatic energy and forces for a collection of charges in doubly-periodic slabs with jumps in the dielectric permittivity at the slab boundaries. Our method achieves spectral accuracy by using…

Numerical Analysis · Mathematics 2021-06-16 Ondrej Maxian , Raul P. Peláez , Leslie Greengard , Aleksandar Donev

Processes with almost periodic covariance functions have spectral mass on lines parallel to the diagonal in the two-dimensional spectral plane. Methods have been given for estimation of spectral mass on the lines of spectral concentration…

Statistics Theory · Mathematics 2008-06-30 Keh-Shin Lii , Murray Rosenblatt

We introduce Statistical Flow Matching (SFM), a novel and mathematically rigorous flow-matching framework on the manifold of parameterized probability measures inspired by the results from information geometry. We demonstrate the…

Machine Learning · Computer Science 2025-11-26 Chaoran Cheng , Jiahan Li , Jian Peng , Ge Liu

Graphical models are widely used to model stochastic dependences among large collections of variables. We introduce a new method of estimating undirected conditional independence graphs based on the score matching loss, introduced by…

Methodology · Statistics 2016-03-24 Lina Lin , Mathias Drton , Ali Shojaie

Representing turbulent flow fields in a compact yet physically faithful form remains a central challenge in computational fluid dynamics. We propose a continuous parametric representation based on localized Gaussian primitives, in which the…

Fluid Dynamics · Physics 2026-04-21 Dhanush Vittal Shenoy , Steven H. Frankel

In this study, we focus on the modelling of coupled systems of shallow water flows and solute transport with source terms due to variable topography and friction effect. Our aim is to propose efficient and accurate numerical techniques for…

Numerical Analysis · Mathematics 2021-10-12 Amine Hanini , Abdelaziz Beljadid , Driss Ouazar

We present the first proof of principle that normalizing flows can accurately learn the Boltzmann distribution of the fermionic Hubbard model - a key framework for describing the electronic structure of graphene and related materials.…

Strongly Correlated Electrons · Physics 2025-06-23 Dominic Schuh , Janik Kreit , Evan Berkowitz , Lena Funcke , Thomas Luu , Kim A. Nicoli , Marcel Rodekamp

This work explores the capability of simulating complex fluid flows by directly solving the Boltzmann equation. Due to the high-dimensionality of the governing equation, the substantial computational cost of solving the Boltzmann equation…

Fluid Dynamics · Physics 2023-12-05 Tarik Dzanic , Luigi Martinelli

Small-angle neutron scattering (SANS) is a powerful technique for probing the nanoscale structure of materials. However, the fundamental limitations of neutron flux pose significant challenges for rapid, high-fidelity data acquisition…

This paper presents an unsupervised algorithm for nonlinear unmixing of hyperspectral images. The proposed model assumes that the pixel reflectances result from a nonlinear function of the abundance vectors associated with the pure spectral…

Machine Learning · Statistics 2015-06-05 Yoann Altmann , Nicolas Dobigeon , Steve McLaughlin , Jean-Yves Tourneret