47 citations · 279 across the 26 of their papers we have counts for
32 papers
Stein's method, Markov processes, and linear eigenvalue statistics of random matrices
David Grzybowski, Mark Meckes
We show how the infinitesimal exchangeable pairs approach to Stein's method combines naturally with the theory of Markov semigroups. We present a multivariate normal approximation…
Magnitude and matrix inequalities
Kiyonori Gomi, Mark Meckes
We present several applications of matrix-theoretic inequalities to the magnitude of metric spaces. We first resolve an open problem by showing that the magnitude of any finite met…
Metric complexity is a Bryant--Tupper diversity
Gautam Aishwarya, Dongbin Li, Mokshay Madiman +1
The metric complexity (sometimes called Leinster--Cobbold maximum diversity) of a compact metric space is a recently introduced isometry-invariant of compact metric spaces which ge…
Magnitude and Holmes-Thompson intrinsic volumes of convex bodies
Mark W. Meckes
Magnitude is a numerical invariant of compact metric spaces, originally inspired by category theory and now known to be related to myriad other geometric quantities. Generalizing e…
Spaces of extremal magnitude
Tom Leinster, Mark Meckes
Magnitude is a numerical invariant of compact metric spaces. Its theory is most mature for spaces satisfying the classical condition of being of negative type, and the magnitude of…
Fluctuations of the spectrum in rotationally invariant random matrix ensembles
Elizabeth S. Meckes, Mark W. Meckes
We investigate traces of powers of random matrices whose distributions are invariant under rotations (with respect to the Hilbert--Schmidt inner product) within a real-linear subsp…