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Wave propagation problems have many applications in physics and engineering, and the stochastic effects are important in accurately modeling them due to the uncertainty of the media. This paper considers and analyzes a fully discrete finite…

Numerical Analysis · Mathematics 2021-06-30 Yukun Li , Shuonan Wu , Yulong Xing

We derive continuous dependence estimates for weak entropy solutions of degenerate parabolic equations with nonlinear fractional diffusion. The diffusion term involves the fractional Laplace operator, $\Delta^{\alpha/2}$ for $\alpha \in…

Analysis of PDEs · Mathematics 2015-10-06 Nathael Alibaud , Simone Cifani , Espen Jakobsen

Theoretical estimates of the convergence rate of many well-known gradient-type optimization methods are based on quadratic interpolation, provided that the Lipschitz condition for the gradient is satisfied. In this article we obtain a…

Optimization and Control · Mathematics 2018-12-18 Fedor S. Stonyakin

We show how the Stefan type free boundary problem with random diffusion in one space dimension can be approximated by the corresponding free boundary problem with nonlocal diffusion. The approximation problem is a slightly modified version…

Analysis of PDEs · Mathematics 2020-03-13 Yihong Du , Wenjie Ni

We compute the first order correction of the effective viscosity for a suspension containing solid particles with arbitrary shapes. We rewrite the computation as an homogenization problem for the Stokes equations in a perforated domain.…

Analysis of PDEs · Mathematics 2019-05-30 Matthieu Hillairet , Di Wu

We analyze the inverse problem of identifying the diffusivity coefficient of a scalar elliptic equation as a function of the resolvent operator. We prove that, within the class of measurable coefficients, bounded above and below by positive…

Analysis of PDEs · Mathematics 2016-12-05 Mourad Choulli , Enrique Zuazua

We propose a sparse regression method based on the non-concave penalized density power divergence loss function which is robust against infinitesimal contamination in very high dimensionality. Present methods of sparse and robust regression…

Methodology · Statistics 2021-05-18 Abhik Ghosh , Subhabrata Majumdar

We revisit the homogenization problem for the Poisson equation in periodically perforated domains with zero Neumann data at the boundary of the holes and prescribed Dirichlet data at the outer boundary. It is known that, if the periodicity…

Analysis of PDEs · Mathematics 2022-02-01 Wenjia Jing

We prove a weak converse estimate for the simultaneous approximation by several forms of the Bernstein polynomials with integer coefficients. It is stated in terms of moduli of smoothness. In particular, it yields a big $O$-characterization…

Classical Analysis and ODEs · Mathematics 2020-09-17 Borislav R. Draganov

In this paper, we present a numerical approach to solve the McKean-Vlasov equations, which are distribution-dependent stochastic differential equations, under some non-globally Lipschitz conditions for both the drift and diffusion…

Numerical Analysis · Mathematics 2023-05-30 Qian Guo , Jie He , Lei Li

The scattering of quasiperiodic waves for a two-dimensional Helmholtz equation with a constant refractive index perturbed by a function which is periodic in one direction and of finite support in the other is considered. The scattering…

Mathematical Physics · Physics 2019-10-23 P. Zhevandrov , A. Merzon , M. I. Romero Rodríguez , J. E. de la Paz Méndez

In this paper, we study the Wong-Zakai approximation of the solution to the stochastic differential equation on a domain $D$ in a Euclidean space with normal reflection at the boundary. We prove the $L^p$ convergence of the approximation in…

Probability · Mathematics 2013-05-27 Shigeki Aida , Kosuke Sasaki

We investigate the convergence rate of the recently proposed subgradient-push method for distributed optimization over time-varying directed graphs. The subgradient-push method can be implemented in a distributed way without requiring…

Optimization and Control · Mathematics 2015-02-17 Angelia Nedic , Alex Olshevsky

We consider a viscous approximation for a nonlinear degenerate convection-diffusion equations in two space dimensions, and prove an $L^1$ error estimate. Precisely, we show that the $L^1_{\mathrm{loc}}$ difference between the approximate…

Analysis of PDEs · Mathematics 2013-11-08 C. Klingenberg , U. Koley

We present a novel artificial diffusion method to circumvent the instabilities associated with the standard finite element approximation of convection-diffusion equations. Motivated by the micromorphic approach, we introduce an auxiliary…

Numerical Analysis · Mathematics 2025-06-19 Soheil Firooz , B. Daya Reddy , Paul Steinmann

We derive the hydrodynamic limit of a kinetic equation with a stochastic, short range perturbation of the velocity operator. Under some mixing hypotheses on the stochastic perturbation, we establish a diffusion-approximation result: the…

Analysis of PDEs · Mathematics 2020-10-01 Nils Caillerie , Julien Vovelle

We find a renormalized "time-dependent diffusion coefficient", D(t), for pulsed excitation of a nominally diffusive sample by solving the Bethe-Salpeter equation with recurrent scattering. We observe a crossover in dynamics in the…

Disordered Systems and Neural Networks · Physics 2009-11-10 S. K. Cheung , X. Zhang , Z. Q. Zhang , A. A. Chabanov , A. Z. Genack

We consider a possibly degenerate porous media type equation over all of $\R^d$ with $d = 1$, with monotone discontinuous coefficients with linear growth and prove a probabilistic representation of its solution in terms of an associated…

Probability · Mathematics 2014-06-30 Viorel Barbu , Michael Roeckner , Francesco Russo

We study functional regression with random subgaussian design and real-valued response. The focus is on the problems in which the regression function can be well approximated by a functional linear model with the slope function being…

Statistics Theory · Mathematics 2014-09-16 Vladimir Koltchinskii , Stanislav Minsker

Flow Matching, a promising approach in generative modeling, has recently gained popularity. Relying on ordinary differential equations, it offers a simple and flexible alternative to diffusion models, which are currently the…

Machine Learning · Statistics 2026-03-13 Lea Kunkel
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