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Score-based diffusion models provide a powerful way to model images using the gradient of the data distribution. Leveraging the learned score function as a prior, here we introduce a way to sample data from a conditional distribution given…

Image and Video Processing · Electrical Eng. & Systems 2022-07-19 Hyungjin Chung , Jong Chul Ye

Driven by the need to solve increasingly complex optimization problems in signal processing and machine learning, there has been increasing interest in understanding the behavior of gradient-descent algorithms in non-convex environments.…

Optimization and Control · Mathematics 2019-07-04 Stefan Vlaski , Ali H. Sayed

The inverse problem of backward diffusion is known to be ill-posed and highly unstable. Backward diffusion processes appear naturally in image enhancement and deblurring applications. It is therefore greatly desirable to establish a…

Numerical Analysis · Mathematics 2020-06-18 Leif Bergerhoff , Marcelo Cárdenas , Joachim Weickert , Martin Welk

In our recent work on iterative computation in hardware, we showed that arbitrary-precision solvers can perform more favorably than their traditional arithmetic equivalents when the latter's precisions are either under- or over-budgeted for…

Numerical Analysis · Mathematics 2020-10-20 He Li , Ian McInerney , James J. Davis , George A. Constantinides

A computational tool for coarse-graining nonlinear systems of ordinary differential equations in time is discussed. Three illustrative model examples are worked out that demonstrate the range of capability of the method. This includes the…

Numerical Analysis · Mathematics 2017-11-23 Sabyasachi Chatterjee , Amit Acharya , Zvi Artstein

In this article we study the numerical approximation of a variable coefficient fractional diffusion equation. Using a change of variable, the variable coefficient fractional diffusion equation is transformed into a constant coefficient…

Numerical Analysis · Mathematics 2019-02-28 Xiangcheng Zheng , V. J. Ervin , Hong Wang

We apply verified numerics to the Nirenberg problem, proving that a genuine solution exists near two given computer-generated approximate solutions. This proves existence of a solution for a particular prescribed curvature that was…

Differential Geometry · Mathematics 2026-04-01 Daniel Platt

We present a simple numerical algorithm for solving elliptic equations where the diffusion coefficient, the source term, the solution and its flux are discontinuous across an irregular interface. The algorithm produces second-order accurate…

Computational Physics · Physics 2023-09-26 Daniil Bochkov , Frederic Gibou

This article focuses on a large family of cross-diffusion systems of the form $\partial$ t U-$\Delta$A(U) = 0, in dimension d $\in$ N * , and where U $\in$ R 2. We show that under natural conditions on the nonlinearity A, those systems have…

Analysis of PDEs · Mathematics 2024-03-04 L Desvillettes , A Moussa

In this paper we construct numerical schemes to approximate linear transport equations with slab geometry by diffusion equations. We treat both the case of pure diffusive scaling and the case where kinetic and diffusive scalings coexist.…

Numerical Analysis · Mathematics 2015-05-18 Qin Li , Jianfeng Lu , Weiran Sun

Source localization is the inverse problem of graph information dissemination and has broad practical applications. However, the inherent intricacy and uncertainty in information dissemination pose significant challenges, and the ill-posed…

Machine Learning · Computer Science 2023-04-19 Bosong Huang , Weihao Yu , Ruzhong Xie , Jing Xiao , Jin Huang

In the study of concavity properties of positive solutions to nonlinear elliptic partial differential equations the diffusion and the nonlinearity are typically independent of the space variable. In this paper we obtain new results aiming…

Analysis of PDEs · Mathematics 2023-09-01 Nouf Almousa , Claudia Bucur , Roberta Cornale , Marco Squassina

Here we study theoretically and compare experimentally an efficient method for solving systems of algebraic equations, where the matrix comes from the discretization of a fractional diffusion operator. More specifically, we focus on…

Numerical Analysis · Mathematics 2020-02-26 Stanislav Harizanov , Raytcho Lazarov , Pencho Marinov , Svetozar Margenov , Joseph Pasciak

Diffusion models have gained prominence as powerful generative tools for solving inverse problems due to their ability to model complex data distributions. However, existing methods typically rely on complete knowledge of the forward…

Machine Learning · Computer Science 2026-03-03 Hongkun Dou , Zike Chen , Zeyu Li , Hongjue Li , Lijun Yang , Yue Deng

We consider the semilinear diffusion equation $\partial$ t u = Au + |u| $\alpha$ u in the half-space R N + := R N --1 x (0, +$\infty$), where A is a linear diffusion operator, which may be the classical Laplace operator, or a fractional…

Analysis of PDEs · Mathematics 2020-04-21 Matthieu Alfaro , Otared Kavian

In this work, an inverse problem in the fractional diffusion equation with random source is considered. Statistical moments are used of the realizations of single point observation $u(x_0,t,\omega).$ We build the representation of the…

Analysis of PDEs · Mathematics 2019-11-04 Chan Liu , Jin Wen , Zhidong Zhang

The use of cross-diffusion systems as mathematical models of different image processes is investigated. The present paper is concerned with linear filtering. First, those systems satisfying the most important scale-space properties are…

Analysis of PDEs · Mathematics 2017-02-21 A. Araujo , S. Barbeiro , E. Cuesta , A. Duran

We consider the numerical solution of the equation - \Delta u - f(u) = g, for the unknown u satisfying Dirichlet conditions in a bounded domain. The nonlinearity f has bounded, continuous derivative. The algorithm uses the finite element…

Analysis of PDEs · Mathematics 2011-04-01 J. Cal Neto , C. Tomei

We provide a `user guide' to the literature of the past twenty years concerning the modeling and approximation of discontinuous solutions to nonlinear hyperbolic systems that admit small-scale dependent shock waves. We cover several classes…

Analysis of PDEs · Mathematics 2013-12-05 Philippe G. LeFloch , Siddhartha Mishra

Diffusion models have emerged as powerful tools for generative modeling, demonstrating exceptional capability in capturing target data distributions from large datasets. However, fine-tuning these massive models for specific downstream…

Machine Learning · Computer Science 2025-09-01 Yinbin Han , Meisam Razaviyayn , Renyuan Xu
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