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We propose a novel type of nonlinear solver acceleration for systems of nonlinear partial differential equations (PDEs) that is based on online/adaptive learning. It is applied in the context of multiphase flow in porous media. The proposed…

Machine Learning · Computer Science 2025-04-28 Vinicius L S Silva , Pablo Salinas , Claire E Heaney , Matthew Jackson , Christopher C Pain

This paper proposes and analyzes a communication-efficient distributed optimization framework for general nonconvex nonsmooth signal processing and machine learning problems under an asynchronous protocol. At each iteration, worker machines…

Optimization and Control · Mathematics 2020-07-15 Jineng Ren , Jarvis Haupt

Parabolic partial differential equations (PDEs) are in ubiquitous, very effective use to model diffusion processes. However, there are many applications (e.g., such as in hydrology, animal foraging, biology, and light diffusion just do name…

Numerical Analysis · Mathematics 2025-09-23 Shiping Zhou , Yanzhi Zhang , Max Gunzburger

We address the inverse problem of identifying a time-dependent potential coefficient in a one-dimensional diffusion equation subject to Dirichlet boundary conditions and a nonlocal integral overdetermination constraint reflecting spatially…

Numerical Analysis · Mathematics 2025-11-12 Arshyn Altybay , Michael Ruzhansky

In this article spatial and temporal regularity of the solution process of a stochastic partial differential equation (SPDE) of evolutionary type with nonlinear multiplicative trace class noise is analyzed.

Probability · Mathematics 2011-11-07 Arnulf Jentzen , Michael Roeckner

Physics-Informed Neural Networks (PINNs) are machine learning tools that approximate the solution of general partial differential equations (PDEs) by adding them in some form as terms of the loss/cost function of a Neural Network. Most…

Numerical Analysis · Mathematics 2022-08-29 Antonio Tadeu Azevedo Gomes , Larissa Miguez da Silva , Frederic Valentin

In this short communication, we announce an algorithmic procedure for constructing non-uniqueness counter-examples of classical solutions to initial-boundary-value problems for a wide class of linear evolution partial differential…

Analysis of PDEs · Mathematics 2025-12-05 Andreas Chatziafratis , Spyridon Kamvissis

A discretization scheme is introduced for a set of convection-diffusion equations with a non-linear reaction term, where the convection velocity is constant for each reactant. This constancy allows a transformation to new spatial variables,…

Computational Physics · Physics 2017-09-19 József Vass , Sergey N. Krylov

The radiation diffusion problem is a kind of {time-dependent} nonlinear equations. For solving the radiation diffusion equations, many linear systems are obtained in the nonlinear iterations at each time step. The cost of linear equations…

Numerical Analysis · Mathematics 2020-02-19 Shuai Ye , Hengbin An , Xinhai Xu

We propose a double obstacle phase field approach to the recovery of piece-wise constant diffusion coefficients for elliptic partial differential equations. The approach to this inverse problem is that of optimal control in which we have a…

Numerical Analysis · Mathematics 2016-04-20 Klaus Deckelnick , Charles M. Elliott , Vanessa Styles

This paper explores the forward and inverse problems for a fractional subdiffusion equation characterized by time-dependent diffusion and reaction coefficients. Initially, the forward problem is examined, and its unique solvability is…

Analysis of PDEs · Mathematics 2025-11-10 Ravshan Ashurov , Elbek Husanov

We study the asymptotic behaviour of a system of nonlinear reaction--diffusion--advection equations in a domain consisting of two bulk regions connected via microscopic channels distributed within a thin membrane. Both the width of the…

Analysis of PDEs · Mathematics 2025-12-15 Lucas M. Fix , Gianna Götzmann , Malte A. Peter , Jan-F. Pietschmann

Inverse problems in partial differential equations (PDEs) involve estimating the physical parameters of a system from observed spatiotemporal solution fields. Neural networks are well-suited for PDE parameter estimation due to their…

Machine Learning · Computer Science 2026-05-27 Divyam Goel , Nithin Chalapathi , Sanjeev Raja , Aditi S. Krishnapriyan

We investigate a nonlocal single-species reaction-diffusion-advection model that integrates the spatial memory of previously visited locations and nonlocal detection in space, resulting in a coupled PDE-ODE system reflective of several…

Analysis of PDEs · Mathematics 2023-10-05 Di Liu , Yurij Salmaniw , Jonathan R. Potts , Junping Shi , Hao Wang

We consider a (sub)diffusion equation with a nonlinearity of the form $pf(u)-qu$, where $p$ and $q$ are space dependent functions. Prominent examples are the Fisher-KPP, the Frank-Kamenetskii-Zeldovich and the Allen-Cahn equations. We…

Numerical Analysis · Mathematics 2026-02-02 Barbara Kaltenbacher , William Rundell

A large class of physically important nonlinear and nonhomogeneous evolution problems, characterized by advection-like and diffusion-like processes, can be usefully studied by a time-differential form of Kolmogorov's solution of the…

Data Analysis, Statistics and Probability · Physics 2007-08-24 R. G. Keanini

This paper is devoted to reaction-diffusion equations with bistable nonlinearities depending periodically on time. These equations admit two linearly stable states. However, the reaction terms may not be bistable at every time. These may…

Analysis of PDEs · Mathematics 2015-07-23 Benjamin Contri

The focus of this paper is a non-local singular non-linear Fokker-Planck partial differential equation (PDE). The peculiarity of this PDE feature is in its divergence coefficient, which presents a product between a Besov distribution and a…

Probability · Mathematics 2026-05-13 Luca Bondi , Elena Issoglio , Francesco Russo

Of primary interest in this paper is the numerical approximation of a time dependent fractional, in space, diffusion equation where the domain is assumed to be nonhomogeneous, having different axial diffusion coefficients. This work is…

Numerical Analysis · Mathematics 2026-05-12 T. Catoe , V. J. Ervin

We consider a partial data inverse problem for a time-dependent convection-diffusion equation on an admissible manifold. We prove that the time-dependent convection term and time-dependent density can be recovered uniquely modulo a known…

Analysis of PDEs · Mathematics 2024-05-03 Rohit Kumar Mishra , Anamika Purohit , Manmohan Vashisth
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