English
Related papers

Related papers: Study on two Methods for Nonlinear Force-free Extr…

200 papers

Basis set extrapolations are typically rationalized either from analytical arguments involving the partial-wave or principal expansions of the correlation energy in helium-like systems, or from fitting extrapolation parameters to reference…

Chemical Physics · Physics 2024-09-09 Vladimir Fishman , Emmanouil Semidalas , Jan M. L. Martin

The structure and function of biological molecules are strongly influenced by the water and dissolved ions that surround them. This aqueous solution (solvent) exerts significant electrostatic forces in response to the biomolecule's…

Numerical Analysis · Mathematics 2015-12-29 Matthew G. Knepley , Jaydeep P. Bardhan

Abbe's resolution limit, one of the best-known physical limitations, poses a great challenge for any wave systems in imaging, wave transport, and dynamics. Originally formulated in linear optics, this Abbe's limit can be broken using…

In this paper, we consider the boundary integral equation (BIE) method for solving the exterior Neumann boundary value problems of elastic and thermoelastic waves in three dimensions based on the Fredholm integral equations of the first…

Numerical Analysis · Mathematics 2019-06-26 Gang Bao , Liwei Xu , Tao Yin

The field of derivative-free optimization (DFO) studies algorithms for nonlinear optimization that do not rely on the availability of gradient or Hessian information. It is primarily designed for settings when functions are black-box,…

Optimization and Control · Mathematics 2025-10-07 Lindon Roberts

Amortized variational inference (AVI) replaces instance-specific local inference with a global inference network. While AVI has enabled efficient training of deep generative models such as variational autoencoders (VAE), recent empirical…

Machine Learning · Statistics 2018-07-25 Yoon Kim , Sam Wiseman , Andrew C. Miller , David Sontag , Alexander M. Rush

In this paper, we introduce a new reduced basis methodology for accelerating the computation of large parameterized systems of high-fidelity integral equations. Core to our methodology is the use of coarse-proxy models (i.e., lower…

Numerical Analysis · Mathematics 2019-11-14 Philip A. Etter , Yuwei Fan , Lexing Ying

High-order numerical methods for solving elliptic equations over arbitrary domains typically require specialized machinery, such as high-quality conforming grids for finite elements method, and quadrature rules for boundary integral…

Numerical Analysis · Mathematics 2021-06-02 Saad Qadeer , Boyce E. Griffith

We generalize the closest point method (CPM) to solve surface partial differential equations with general boundary conditions. The proposed extrapolation method provides a unified framework for treating a broad class of inhomogeneous…

Numerical Analysis · Mathematics 2025-11-25 Tony Wong , Colin B. Macdonald , Byungjoon Lee

In this work, we implement a relatively new analytical technique, the Improved Amplitude-Frequency Formulation (IAFF) method, approach for solving accurate approximate analytical solutions for strong nonlinear oscillators, which may contain…

Dynamical Systems · Mathematics 2021-10-05 R. Azami , D. D. Ganji , A. G. Davodi , H. Babazadeh

The estimation of the Extreme Value Index (EVI) is fundamental in extreme value analysis but suffers from high variance due to reliance on only a few extreme observations. We propose a control variates based transfer learning approach in a…

Methodology · Statistics 2025-11-20 Louison Bocquet-Nouaille , Jérôme Morio , Benjamin Bobbia

We describe a strategy for solving nonlinear eigenproblems numerically. Our approach is based on the approximation of a vector-valued function, defined as solution of a non-homogeneous version of the eigenproblem. This approximation step is…

Numerical Analysis · Mathematics 2023-12-06 Davide Pradovera

Reject Inference (RI) methods aim to address sample bias by inferring missing repayment data for rejected credit applicants. Traditional approaches often assume that the behavior of rejected clients can be extrapolated from accepted…

Machine Learning · Computer Science 2025-10-16 Athyrson Machado Ribeiro , Marcos Medeiros Raimundo

Automatic Differentiation Variational Inference (ADVI) is efficient in learning probabilistic models. Classic ADVI relies on the parametric approach to approximate the posterior. In this paper, we develop a spline-based nonparametric…

Machine Learning · Statistics 2024-03-12 Yuda Shao , Shan Yu , Tianshu Feng

The presence of measurement error is a widespread issue which, when ignored, can render the results of an analysis unreliable. Numerous corrections for the effects of measurement error have been proposed and studied, often under the…

Methodology · Statistics 2023-06-29 Dylan Spicker , Michael Wallace , Grace Yi

We consider parameter estimation and inference when data feature blockwise, non-monotone missingness. Our approach, rooted in semiparametric theory and inspired by prediction-powered inference, leverages off-the-shelf AI (predictive or…

Methodology · Statistics 2025-09-30 Qi Xu , Lorenzo Testa , Jing Lei , Kathryn Roeder

Approximate Bayesian computation (ABC) methods make use of comparisons between simulated and observed summary statistics to overcome the problem of computationally intractable likelihood functions. As the practical implementation of ABC…

Methodology · Statistics 2013-06-12 M. G. B. Blum , M. A. Nunes , D. Prangle , S. A. Sisson

GUI grounding is a critical capability for enabling GUI agents to execute tasks such as clicking and dragging. However, in complex scenarios like the ScreenSpot-Pro benchmark, existing models often suffer from suboptimal performance.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Borui Zhang , Bo Zhang , Bo Wang , Wenzhao Zheng , Yuhao Cheng , Liang Tang , Yiqiang Yan , Jie Zhou , Jiwen Lu

Calculations in field theory are usually accomplished by employing some variants of perturbation theory, for instance using loop expansions. These calculations result in asymptotic series in powers of small coupling parameters, which as a…

High Energy Physics - Phenomenology · Physics 2021-05-05 V. I. Yukalov , E. P. Yukalova

In this dissertation, we analytically study the apex field enhancement factor (FEF), $\gamma_a$, by constructing a method which consists in minimizing an error function defined as to measure the deviation of the potential at the boundary,…

Classical Physics · Physics 2019-09-24 Adson Soares de Souza