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Interferometers play an increasingly important role for spatially resolved observations. If employed at full potential, interferometry can probe an enormous dynamic range in spatial scale. Interpretation of the observed visibilities…

Instrumentation and Methods for Astrophysics · Physics 2015-06-19 C. Brinch , C. P. Dullemond

Interpolation for scattered data is a classical problem in numerical analysis, with a long history of theoretical and practical contributions. Recent advances have utilized deep neural networks to construct interpolators, exhibiting…

Machine Learning · Computer Science 2023-03-15 Shizhe Ding , Boyang Xia , Milong Ren , Dongbo Bu

We propose a novel Riemannian geometric framework for variational inference in Bayesian models based on the nonparametric Fisher-Rao metric on the manifold of probability density functions. Under the square-root density representation, the…

Methodology · Statistics 2019-03-29 Abhijoy Saha , Karthik Bharath , Sebastian Kurtek

This paper addresses the problems of spline interpolation on smooth Riemannian manifolds, with or without the inclusion of least-squares fitting. Our unified approach utilizes gradient flows for successively connected curves or networks,…

Optimization and Control · Mathematics 2025-10-29 Chun-Chi Lin , Dung The Tran

We propose a new method for smoothly interpolating probability measures using the geometry of optimal transport. To that end, we reduce this problem to the classical Euclidean setting, allowing us to directly leverage the extensive toolbox…

In this work, we consider the bilevel optimization problem on Riemannian manifolds. We inspect the calculation of the hypergradient of such problems on general manifolds and thus enable the utilization of gradient-based algorithms to solve…

Optimization and Control · Mathematics 2024-02-09 Jiaxiang Li , Shiqian Ma

In this paper we study the Dirichlet problem for a class of Hessian type equation with its structure as a combination of elementary symmetric functions on Hermitian manifolds. Under some conditions with the initial data on manifolds and…

Analysis of PDEs · Mathematics 2022-01-14 Qiang Tu , Ni Xiang

In this paper, we investigate the approximation properties of two types of multiscale finite element methods with oversampling as proposed in [Hou \& Wu, {\textit{J. Comput. Phys.}}, 1997] and [Efendiev, Hou \& Wu, \textit{SIAM J. Numer.…

Numerical Analysis · Mathematics 2025-07-22 Guanglian Li

Entanglement of bipartite squeezed states generated by holomorphic Hermite functions of two complex variables is investigated using phase-space approach based on the Wigner distribution function. Orthogonality of the holomorphic Hermite…

Quantum Physics · Physics 2025-08-15 K. Górska , A. Horzela , D. Kołaczek , B. J. Spisak , F. H. Szafraniec

Partial Differential Equations (PDEs) are fundamental for modeling physical systems, yet solving them in a generic and efficient manner using machine learning-based approaches remains challenging due to limited multi-input and multi-scale…

Machine Learning · Computer Science 2025-08-12 Yichen Luo , Jia Wang , Dapeng Lan , Yu Liu , Zhibo Pang

This work is concerned with spectral collocation methods for fractional PDEs in unbounded domains. The method consists of expanding the solution with proper global basis functions and imposing collocation conditions on the Gauss-Hermite…

Numerical Analysis · Mathematics 2018-01-30 Tao Tang , Huifang Yuan , Tao Zhou

Exploiting the variational interpretation of kernel interpolation we exhibit a direct connection between interpolation and regression, where interpolation appears as a limiting case of regression. By applying this framework to point clouds…

Numerical Analysis · Mathematics 2026-02-09 Patrick Guidotti

This paper investigates the mean square error optimal estimation of scale invariant Wigner spectrum for the class of Gaussian locally self-similar processes, by the multitaper method. In this method, the spectrum is estimated as a weighted…

Probability · Mathematics 2017-12-11 Yasaman Maleki

Port-Hamiltonian systems result from port-based network modeling of physical systems and are an important example of passive state-space systems. In this paper, we develop the framework for model reduction of large-scale…

Numerical Analysis · Mathematics 2015-03-17 Serkan Gugercin , Rostyslav V. Polyuga , Christopher Beattie , Arjan van der Schaft

Present day electromagnetic field calculations have limitations that are due to techniques employing edge-based discretization methods. While these vector finite element methods solve the issues of tangential continuity of fields and the…

Computational Physics · Physics 2019-12-11 Dung N. Pham , Sathwik Bharadwaj , L. R. Ram-Mohan

Bayesian methods are developed for the multivariate nonparametric regression problem where the domain is taken to be a compact Riemannian manifold. In terms of the latter, the underlying geometry of the manifold induces certain symmetries…

Statistics Theory · Mathematics 2007-06-13 Jean-François Angers , Peter T. Kim

This work investigates finite differences and the use of interpolation models to obtain approximations to the first and second derivatives of a function. Here, it is shown that if a particular set of points is used in the interpolation…

Optimization and Control · Mathematics 2020-01-24 Ian D. Coope , Rachael Tappenden

In this work we present a variant of the fast multipole method (FMM) for efficiently evaluating standard layer potentials on geometries with complex coordinates in two and three dimensions. The complex scaled boundary integral method for…

Numerical Analysis · Mathematics 2025-10-20 Tristan Goodwill , Leslie Greengard , Jeremy Hoskins , Manas Rachh , Yuguan Wang

We propose a Hermite spectral method for the spatially inhomogeneous Boltzmann equation. For the inverse-power-law model, we generalize an approximate quadratic collision operator defined in the normalized and dimensionless setting to an…

Spectral Theory · Mathematics 2019-02-26 Zhicheng Hu , Zhenning Cai , Yanli Wang

In this paper, we study an additive model where the response variable is Hilbert-space-valued and predictors are multivariate Euclidean, and both are possibly imperfectly observed. Considering Hilbert-space-valued responses allows to cover…

Statistics Theory · Mathematics 2022-12-13 Jeong Min Jeon , Germain Van Bever