Results 111 to 120 of about 2,057 (240)
Neural network augmented inverse problems for PDEs
, 2017 In this paper we show how to augment classical methods for inverse problems with artificial neural networks. The neural network acts as a prior for the coefficient to be estimated from noisy data. Neural networks are global, smooth function approximators and as such they do not require explicit regularization of the error functional to recover smooth ...
Berg, Jens, Nyström, Kaj
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Multigrid Algorithms for Inverse Problems with Linear Parabolic PDE Constraints
SIAM Journal on Scientific Computing, 2008 We present a multigrid algorithm for the solution of source identification inverse problems constrained by variable-coefficient linear parabolic partial differential equations. We consider problems in which the inversion variable is a function of space only. We consider the case of $L^2$ Tikhonov regularization. The convergence rate of our algorithm is
Adavani, Santi S, Biros, George
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Small Structures, Volume 7, Issue 8, August 2026.Anodic aluminum oxide (AAO) templates combined with atomic layer deposition (ALD) constitute a synergistic platform for engineering functional nanostructures within highly ordered, high‐aspect‐ratio porous architectures. By linking precursor transport modeling, surface chemistry control, and tailored ALD strategies, this review establishes a unified ...
Hyeon Joon Choi +7 more
wiley +1 more source
Compressed sensing for inverse problems [PDF]
Inverse problems are fundamental in many areas of science and engineering, yet their theoretical analysis often assumes access to an infinite number of measurements.
FELISI, ALESSANDRO
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Optimal scaling and diffusion limits for the Langevin algorithm in high dimensions [PDF]
, 2011 The Metropolis-adjusted Langevin (MALA) algorithm is a sampling algorithm which makes local moves by incorporating information about the gradient of the target density. In this paper we study the efficiency of MALA on a natural class of target measures
Thiéry, Alexandre H. +3 more
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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
doaj +1 more source
Small Structures, Volume 7, Issue 8, August 2026.This review discusses the integration of advanced characterization, computational modeling, and multifunctional atmospheric water harvesting (AWH) systems for sustainable water‐energy‐carbon solutions. These methods reveal structure‐property relationships, guiding next‐generation hygroscopic material design.
Miao Tang, Huan Liu, Mitch Guijun Li
wiley +1 more source
International Journal of Geo-EngineeringThe accurate modeling of water and heat transport in soils is crucial for both geo-environmental and geothermal engineering. Traditional modeling methods are problematic because they require well-defined boundaries and initial conditions.
Yuan Feng +3 more
doaj +1 more source
AerospaceA model-based method has been developed for the performance simulation and conceptual design of rocket-type pulse detonation engines (PDEs). A reduced-order model (ROM) has been generated based on the high order singular value decomposition of a data ...
Luis Sánchez de León +3 more
doaj +1 more source
Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.Abstract Physics‐Informed Neural Networks (PINNs) have emerged as a powerful framework for modeling groundwater flow using deep learning neural networks, particularly in scenarios where traditional data‐driven approaches are limited by the scarcity of data.
Adhish Virupaksha +4 more
wiley +1 more source