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Low-rank approximations for parametric and random PDEs

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UNQW01 - Key UQ methodologies and motivating applications

The first part of this talk gives an introduction to low-rank tensors as a general tool for approximating high-dimensional functions. The second part deals with their application to partial differential equations with many parameters, as they arise in particular in uncertainty quantification problems. Here the focus is on error and complexity guarantees, as well as on low-rank approximability of solutions.

This talk is part of the Isaac Newton Institute Seminar Series series.

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