Results 91 to 100 of about 35,012 (233)
Two Scale FE‐FFT‐Based Modeling of Cancellous Bone
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.ABSTRACT Osteoporosis is characterized by a loss of volume percentage of cortical bone, which reduces the loading capacity of this organ and increases its likelihood for fractures. The disease has the highest prevalence of any bone disease worldwide, with a particularly high incidence among the elderly.
Mischa Blaszczyk +3 more
wiley +1 more source
IEEE AccessWe propose Jacobian-AIME, a novel explanation framework for Physics-Informed Neural Networks (PINNs). PINNs map coordinates to physical fields governed by PDEs.
Kosuke Yano +2 more
doaj +1 more source
Unifying and extending diffusion models through PDEs for solving inverse problems
Computer Methods in Applied Mechanics and EngineeringDiffusion models have emerged as powerful generative tools with applications in computer vision and scientific machine learning (SciML), where they have been used to solve large-scale probabilistic inverse problems. Traditionally, these models have been derived using principles of variational inference, denoising, statistical signal processing, and ...
Agnimitra Dasgupta +6 more
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On MAP Estimates and Source Conditions for Drift Identification in SDEs
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.ABSTRACT We consider the inverse problem of identifying the drift in an stochastic differential equation (SDE) from n$n$ observations of its solution at M+1$M+1$ distinct time points. We derive a corresponding maximum a posteriori (MAP) estimate, we prove differentiability properties as well as a so‐called tangential cone condition for the forward ...
Daniel Tenbrinck +3 more
wiley +1 more source
Inverse problems for semilinear elliptic PDE with a general nonlinearity $a(x,u)$ [PDF]
, 2023 David Johansson +2 more
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AIChE Journal, Volume 72, Issue 5, May 2026.Abstract Despite extensive modeling efforts in extraction research, transient column models are rarely applied in industry due to concerns regarding parameter identifiability and model reliability. To address this, we analyzed uncertainty propagation from estimated parameters in a previously introduced column model and assessed identifiability via ill ...
Andreas Palmtag +2 more
wiley +1 more source
Wasit Journal of Computer and Mathematics ScienceThis paper addresses the inverse problem of reconstructing complete steady-state solutions for elliptic partial differential equations when boundary information is incomplete a situation common in electromagnetic, thermal, and geophysical modeling where ...
ABBAS ALDNADOI
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Remarks on control and inverse problems for PDEs
SeMA JournalAbstract This paper deals with recent results and open questions on the control and parameter identification of systems governed by PDEs. Among them, we find a few parabolic and hyperbolic equations, sometimes in the framework of a free-boundary problem. In the considered control problems, we try to govern the behavior of the solution(s) with
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Physics-Informed Deep Inverse Operator Networks for Solving PDE Inverse Problems
Inverse problems involving partial differential equations (PDEs) can be seen as discovering a mapping from measurement data to unknown quantities, often framed within an operator learning approach. However, existing methods typically rely on large amounts of labeled training data, which is impractical for most real-world applications.
Cho, Sung Woong, Son, Hwijae
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Theoretical and numerical results for some inverse problems for PDEs
, 2021 We consider geometric inverse problems concerning the one-dimensional Burgers equation and some related nonlinear systems (involving heat effects and variable density). In these problems, the goal is to find the size of the spatial interval from some appropriate boundary observations of the solution.
Apraiz, Jone +3 more
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