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We propose an adaptive importance sampling scheme for Gaussian approximations of intractable posteriors. Optimization-based approximations like variational inference can be too inaccurate while existing Monte Carlo methods can be too slow.…

Computation · Statistics 2025-02-04 Willem van den Boom , Andrea Cremaschi , Alexandre H. Thiery

Functional data analysis is a fast evolving branch of modern statistics and the functional linear model has become popular in recent years. However, most estimation methods for this model rely on generalized least squares procedures and…

Methodology · Statistics 2020-06-24 Ioannis Kalogridis , Stefan Van Aelst

We extend the notion of numerical stability of finite difference approximations to include hyperbolic systems that are first order in time and second order in space, such as those that appear in Numerical Relativity. By analyzing the symbol…

General Relativity and Quantum Cosmology · Physics 2009-11-11 Gioel Calabrese , Ian Hinder , Sascha Husa

For a second-order linear differential equation with two irregular singular points of rank three, multiple Laplace-type contour integral solutions are considered. An explicit formula in terms of the Stokes multipliers is derived for the…

Classical Analysis and ODEs · Mathematics 2015-06-26 Wolfgang Buehring

We introduce a numerical method for solving Grad's moment equations or regularized moment equations for arbitrary order of moments. In our algorithm, we do not need explicitly the moment equations. As an instead, we directly start from the…

Mathematical Physics · Physics 2010-05-04 Zhenning Cai , Ruo Li

Stochastic differential equations are widely used in various fields; in particular, the usefulness of duality relations has been demonstrated in some models such as population models and Brownian momentum processes. In this study, a…

Statistical Mechanics · Physics 2021-02-09 Jun Ohkubo

The doubly robust (DR) estimator, which consists of two nuisance parameters, the conditional mean outcome and the logging policy (the probability of choosing an action), is crucial in causal inference. This paper proposes a DR estimator for…

Machine Learning · Computer Science 2021-06-22 Masahiro Kato , Shota Yasui , Kenichiro McAlinn

In numerical simulations of many charged systems at the micro/nano scale, a common theme is the repeated solution of the Poisson-Boltzmann equation. This task proves challenging, if not entirely infeasible, largely due to the nonlinearity…

Numerical Analysis · Mathematics 2018-08-29 Lijie Ji , Yanlai Chen , Zhenli Xu

We propose a flexible approach for computing the resolvent of the sum of weakly monotone operators in real Hilbert spaces. This relies on splitting methods where strong convergence is guaranteed. We also prove linear convergence under…

Optimization and Control · Mathematics 2018-09-12 Minh N. Dao , Hung M. Phan

In this paper we prove dispersive estimates for the system formed by two coupled discrete Schr\"odinger equations. We obtain estimates for the resolvent of the discrete operator and prove that it satisfies the limiting absorption principle.…

Analysis of PDEs · Mathematics 2010-07-27 L. I. Ignat , D. Stan

Many statistical problems involve mixture models and the need for computationally efficient methods to estimate the mixing distribution has increased dramatically in recent years. Newton [Sankhya Ser. A 64 (2002) 306--322] proposed a fast…

Methodology · Statistics 2011-02-18 Ryan Martin , Jayanta K. Ghosh

We consider mixed finite element approximation of a singularly perturbed fourth-order elliptic problem with two different boundary conditions, and present a new measure of the error, whose components are balanced with respect to the…

Numerical Analysis · Mathematics 2016-09-16 Shaohong Du , Runchang Lin , Zhimin Zhang

We present a novel method for precise numerical solution of the irreducible two-body problem and apply it to excitons in solids. The approach is based on the Monte Carlo simulation of the two-body Green function specified by Feynman's…

Strongly Correlated Electrons · Physics 2009-11-07 E. A. Burovski , A. S. Mishchenko , N. V. Prokof'ev , B. V. Svistunov

Starting from Boltzmann equation with relaxation time approximation for the collision term and using Chapman-Enskog like expansion for distribution function close to equilibrium, we derive hydrodynamic evolution equations for the…

Nuclear Theory · Physics 2013-05-22 Amaresh Jaiswal

We develop a randomized Newton's method for solving differential equations, based on a fully connected neural network discretization. In particular, the randomized Newton's method randomly chooses equations from the overdetermined nonlinear…

Numerical Analysis · Mathematics 2019-12-09 Qipin Chen , Wenrui Hao

This article describes a method for constructing approximations to periodic solutions of dynamic Lorenz system with classical values of the system parameters. The author obtained a system of nonlinear algebraic equations in general form…

Numerical Analysis · Mathematics 2021-02-10 Alexander N. Pchelintsev

Discretization of non-linear Poisson-Boltzmann Equation equations results in a system of non-linear equations with symmetric Jacobian. The Newton algorithm is the most useful tool for solving non-linear equations. It consists of solving a…

Mathematical Physics · Physics 2007-05-23 Sanjay Kumar Khattri

The paper starts with a concise description of the recently developed semismooth* Newton method for the solution of general inclusions. This method is then applied to a class of variational inequalities of the second kind. As a result, one…

Optimization and Control · Mathematics 2020-07-23 Helmut Gfrerer , Jiri V. Outrata , Jan Valdman

[Inserted by J. Maurice Rojas] We give a formula for the number of complex roots of a generic system of two polynomial equations in two unknowns. The formula is completely combinatorial, ultimately depending just on the convex hull of the…

History and Overview · Mathematics 2007-05-23 Ferdinand Minding

In many instances, the application of approximate Bayesian methods is hampered by two practical features: 1) the requirement to project the data down to low-dimensional summary, including the choice of this projection, which ultimately…

Methodology · Statistics 2020-06-26 David T. Frazier