Results 61 to 70 of about 2,057 (240)
Deep Neural Networks motivated by PDEs [PDF]
, 2020 One of the most promising areas in artificial intelligence is deep learning, a form of machine learning that uses neural networks containing many hidden layers. Recent success has led to breakthroughs in applications such as speech and image recognition.
Ruthotto, Lars
core
Anisotropic variational models and PDEs for inverse imaging problems [PDF]
, 2019 In this thesis we study new anisotropic variational regularisers and partial differential equations (PDEs) for solving inverse imaging problems that arise in a variety of real-world applications. Firstly, we introduce a new anisotropic higher-order total
core +2 more sources
Advanced Intelligent Discovery, EarlyView.This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
wiley +1 more source
Particle methods for Bayesian inverse problems governed by partial differential equations (PDEs) [PDF]
, 2022 Inverse problems enable integration of observational and experimental data, simulations and/or mathematical models to make scientific predictions. Solving an inverse problem with the Bayesian framework requires exploring a high dimensional, non-Gaussian ...
Myers, Aaron Noah
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Earth, Planets and SpaceMany physical systems are described by partial differential equations (PDEs), and solving these equations and estimating their coefficients or boundary conditions (BCs) from observational data play a crucial role in understanding the associated phenomena.
Tomohisa Okazaki
doaj +1 more source
Toward Intelligent Multimodal Holography for Real‐Time Chemical Imaging of Dynamic Ion Separation
Advanced Intelligent Discovery, EarlyView.Intelligent multimodal holography integrates digital off‐axis holography, spectroscopic imaging, and AI‐driven reconstruction to visualize ion transport and chemical dynamics in real time. In this perspective paper, we outline how this approach enables label‐free, chemically specific monitoring of complex environments and discuss its potential to ...
Giovanna Ricchiuti +3 more
wiley +1 more source
Collage-type approach to inverse problems for elliptic PDEs on perforated domains
Electronic Journal of Differential Equations, 2015 We present a collage-based method for solving inverse problems for elliptic partial differential equations on a perforated domain. The main results of this paper establish a link between the solution of an inverse problem on a perforated domain and ...
Herb E. Kunze, Davide La Torre
doaj
Asia-Pacific Journal of Chemical Engineering, EarlyView.ABSTRACT This article investigates the Soret–Dufour cross‐diffusion effects on radiation‐absorptive unsteady free‐convection of magnetized nanofluids (TiO2–water$$ {\mathrm{TiO}}_2\hbox{--} \mathrm{water} $$ and Cu–water$$ \mathrm{Cu}\hbox{--} \mathrm{water} $$) flow over a vertical moving permeable plate.
B. Prabhakar Reddy +2 more
wiley +1 more source
On Multiscale and Statistical Numerical Methods for PDEs and Inverse Problems [PDF]
, 2023 This thesis focuses on numerical methods for scientific computing and scientific machine learning, specifically on solving partial differential equations and inverse problems. The design of numerical algorithms usually encompasses a spectrum that ranges
Chen, Yifan
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Deep Underground Science and Engineering, EarlyView.This review elucidates the velocity–dispersion–attenuation coupling mechanisms of wave propagation in rock masses, compares six representative models, and reveals how pressure, temperature, mineral composition, and anisotropy jointly control dynamic responses in complex geological media.
Jiajun Shu +8 more
wiley +1 more source