Paper on Approximation properties of slice-matching operators

Shiying’s and Caroline’s paper “Approximation properties of slice-matching operators” is available on the arXiv. In this paper we iterative slicing-and-matching schemes, in particular, the approximation power of one step of such schemes. We show an invariance and an equivariance property with respect to global rigid transformations, approximation of the target measure, and derive a connection… Continue reading Paper on Approximation properties of slice-matching operators

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Paper on stochastic slicing and matching

A preprint of Shiying’s and Caroline’s paper “Measure transfer via stochastic slicing and matching” is available on the arXiv. In this paper we discuss an iterative slicing-and-matching procedure which can be used for measure approximation. This scheme has first been introduced by PitiĆ© et. al.; we show a convergence proof of a stochastic version.

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Data science seed grant

Caroline, together with Shahar Kovalsky, Martin Styner, and Guorong Wu received a seed grant from the School of Data Science and Society at UNC. Our award on “Spatio-temporal analysis of brain functional connectome” will run until June 2024. Official announcement Abstract: We will develop mathematical models and algorithms for the analysis and statistical characterization of… Continue reading Data science seed grant

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New paper

Preprint of our new paper “Linearized Wasserstein dimensionality reduction with approximation guarantees” is available on the arXiv. This is joint work with Alex Cloninger, Keaton Hamm, and Varun Khurana.

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SIAM SEAS

Caroline, Shira Faigenbaum (Duke) and Sorin Mitran (UNC Chapel Hill) are organizing a mini-symposium on “Non-linear stochastic data assimilation – theory and applications” at this year’s SIAM SEAS. The meeting will be held at Virginia Tech, March 25-26, 2023.