In this paper we consider discrete inverse problems for which noise becomes negligible compared to data with increasing model norm. We introduce two novel definitions of regularization for ...
Computational Inverse Problems are all about the application. The driving question is how to extend the thorough theory of an Inverse Problem to an algorithm, which can be implemented and ultimately ...
https://doi.org/10.15609/annaeconstat2009.128.0203 • https://www.jstor.org/stable/10.15609/annaeconstat2009.128.0203 We propose a new method for constructing ...
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AI techniques excel at solving complex equations in physics, especially inverse problems
Differential equations are fundamental tools in physics: they are used to describe phenomena ranging from fluid dynamics to general relativity. But when these equations become stiff (i.e. they involve ...
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