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TTUQ

Uncertainty quantification using tensor train decomposition and polynomial chaos expansion.

If you use this code, please cite this paper

References

This work uses the tensor train codes in randomizedTT, https://github.com/SAMSI-RandTensors/randomizedTT, Al Daas, Hussam, et al. "Randomized algorithms for rounding in the tensor-train format." SIAM Journal on Scientific Computing 45.1 (2023): A74-A95.

The Newton optimization method is based on the Riemannian gradient descent, Steinlechner, Michael. "Riemannian optimization for high-dimensional tensor completion." SIAM Journal on Scientific Computing 38.5 (2016): S461-S484.

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