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Abstract: In this talk, we will describe a well/ill-posedness result for the 2D incompressible Euler equations. We investigate solutions in a setting logarithmically smoother than previously done, in a hope […]
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Applied Math Seminar
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Abstract: We study the optimization of Steklov eigenvalues with respect to a boundary density function ρ on a bounded Lipschitz domain. We investigate the minimization and maximization of a Steklov […] |
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Abstract: Turbulence influences our lives in a multitude of ways, ranging from the mundane (when we stir milk into our coffee) to the spectacular (the formation of galaxies). It is […] |
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From ICON to GenICON: In-Context Operator Learning with Uncertainty Quantification (Siting Liu, UCR)
From ICON to GenICON: In-Context Operator Learning with Uncertainty Quantification (Siting Liu, UCR)
Abstract: I will introduce In-Context Operator Networks (ICON), a framework in which a single neural network learns solution operators for differential equations directly from a few prompted input-output examples at […] |
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