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Fourth-order accurate compact schemes for variable coefficient convection diffusion equations are considered. A sufficient condition for the stability of the fully discrete problem is derived using a difference equation based approach. The…

Numerical Analysis · Mathematics 2024-01-30 Anindya Goswami , Kuldip Singh Patel , Pradeep Kumar Sahu

We consider the inverse problem of reconstructing the scattering and absorption coefficients using boundary measurements for a time dependent radiative transfer equation (RTE). As the measurement is mostly polluted by errors, both…

Numerical Analysis · Mathematics 2017-08-11 Ke Chen , Qin Li , Li Wang

We consider the inverse Calder\'on problem consisting of determining the conductivity inside a medium by electrical measurements on its surface. Ideally, these measurements determine the Dirichlet-to-Neumann map and, therefore, one usually…

Analysis of PDEs · Mathematics 2017-06-28 Pedro Caro , Andoni Garcia

The forward problems of pattern formation have been greatly empowered by extensive theoretical studies and simulations, however, the inverse problem is less well understood. It remains unclear how accurately one can use images of pattern…

Computational Physics · Physics 2021-04-07 Hongbo Zhao , Richard D. Braatz , Martin Z. Bazant

In this paper we study the inverse problem of identifying the diffusion matrix in an elliptic PDE from measurements. The convex energy functional method with Tikhonov regularization is applied to tackle this problem. For the discretization…

Numerical Analysis · Mathematics 2017-09-15 Michael Hinze , Tran Nhan Tam Quyen

The inverse problem methodology is a commonly-used framework in the sciences for parameter estimation and inference. It is typically performed by fitting a mathematical model to noisy experimental data. There are two significant sources of…

Numerical Analysis · Mathematics 2018-07-26 John T. Nardini , D. M. Bortz

The inverse diffusion curve problem focuses on automatic creation of diffusion curve images that resemble user provided color fields. This problem is challenging since the 1D curves have a nonlinear and global impact on resulting color…

Graphics · Computer Science 2016-10-11 Shuang Zhao , Fredo Durand , Changxi Zheng

In this work we derive a posteriori error estimates for the convection-diffusion-reaction equation coupled with the Darcy-Forchheimer problem by a nonlinear external source depending on the concentration of the fluid. We introduce the…

Numerical Analysis · Mathematics 2022-12-27 Toni Sayah , Georges Semaan , Faouzi Triki

Under consideration are mathematical models of heat and mass transfer. We study inverse problems of recovering lower-order coefficients in a second order parabolic equation. The coefficients are representable in the form of a finite…

Analysis of PDEs · Mathematics 2024-12-23 S. G. Pyatkov , O. A. Soldatov

Determining kinetic rate constants is a highly relevant problem in biochemistry, so various methods have been designed to extract them from experimental data. Such methods have two main components: the experimental apparatus and the…

Quantitative Methods · Quantitative Biology 2017-08-04 József Vass , Sergey N. Krylov

These lecture notes summarize various summer schools that I have given on the topic of solving inverse problems (state and parameter estimation) by combining optimally measurement observations and parametrized PDE models. After defining a…

Numerical Analysis · Mathematics 2022-03-16 Olga Mula

We consider the problem of making nonparametric inference in a class of multi-dimensional diffusions in divergence form, from low-frequency data. Statistical analysis in this setting is notoriously challenging due to the intractability of…

Methodology · Statistics 2025-01-23 Matteo Giordano , Sven Wang

We consider the numerical approximation of the ill-posed data assimilation problem for stationary convection-diffusion equations and extend our previous analysis in [Numer. Math. 144, 451--477, 2020] to the convection-dominated regime.…

Numerical Analysis · Mathematics 2022-02-22 Erik Burman , Mihai Nechita , Lauri Oksanen

We propose a variant of the classical conditional gradient method for sparse inverse problems with differentiable measurement models. Such models arise in many practical problems including superresolution, time-series modeling, and matrix…

Optimization and Control · Mathematics 2015-07-07 Nicholas Boyd , Geoffrey Schiebinger , Benjamin Recht

In this paper we introduce the functional framework and the necessary conditions for the well-posedness of an inverse problem arising in the mathematical modeling of disease transmission. The direct problem is given by an initial boundary…

Analysis of PDEs · Mathematics 2018-11-08 Aníbal Coronel , Luis Friz , Ian Hess , María Zegarra

In this article a two-sided variable coefficient fractional diffusion equation (FDE) is investigated, where the variable coefficient occurs outside of the fractional integral operator. Under a suitable transformation the variable…

Numerical Analysis · Mathematics 2018-11-05 Xiangcheng Zheng , V. J. Ervin , Hong Wang

We describe an exact and highly efficient numerical algorithm for solving a special but important class of convection-diffusion equations. These equations occur in many problems in physics, chemistry, or biology, and they are usually hard…

Computational Physics · Physics 2019-03-27 Narain Karedla , Jan Christoph Thiele , Ingo Gregor , Jörg Enderlein

The fractional Calder\'on problem asks to determine the unknown coefficients in a nonlocal, elliptic equation of fractional order from exterior measurements of its solutions. There has been substantial work on many aspects of this inverse…

Analysis of PDEs · Mathematics 2024-08-27 Giovanni Covi

A class of inverse problems for restoring the right-hand side of a parabolic equation for a large class of positive operators with discrete spectrum is considered. The results on existence and uniqueness of solutions of these problems as…

Analysis of PDEs · Mathematics 2019-11-12 Michael Ruzhansky , Niyaz Tokmagambetov , Berikbol T. Torebek

This paper gives direct derivations of the differential equations and likelihood formulas of diffusion models assuming only knowledge of Gaussian distributions. A VAE analysis derives both forward and backward stochastic differential…

Machine Learning · Computer Science 2023-03-07 David McAllester