Jonathan Niles-Weed

works on

bias delocalization 1 hamiltonian monte carlo 1 high-dimensional sampling 1 underdamped langevin 1 Wasserstein distance 1

From the 1 of 3 linked papers with an AI index.

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math.PR2026

Nearly sharp comparison results for sliced and max-sliced Wasserstein distances

Jonathan Niles-Weed, Jacob Shkrob

We prove new comparison results between the Wasserstein distance and its sliced and max-sliced counterparts. First, we show that the Hölder exponent~ $\frac{2}{d + 2}$ obtained by Bob…

math.PR2024

Central Limit Theorems for Smooth Optimal Transport Maps

Tudor Manole, Sivaraman Balakrishnan, Jonathan Niles-Weed +1

One of the central objects in the theory of optimal transport is the Brenier map: the unique monotone transformation which pushes forward an absolutely continuous probability law o…