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Found 4 papers, 0 papers with code
Wasserstein Archetypal Analysis
We prove a consistency result for the regularized problem, ensuring that if the data are iid samples from a probability measure, then as the number of samples is increased, a subsequence of the archetype points converges to the archetype points for the limiting data distribution, almost surely.
A blob method for inhomogeneous diffusion with applications to multi-agent control and sampling
As a consequence of our convergence result, we identify conditions on the target function and data distribution for which convexity of the energy landscape emerges in the continuum limit.
Clustering dynamics on graphs: from spectral clustering to mean shift through Fokker-Planck interpolation
In this work we build a unifying framework to interpolate between density-driven and geometry-based algorithms for data clustering, and specifically, to connect the mean shift algorithm with spectral clustering at discrete and continuum levels.
Linearized Optimal Transport for Collider Events
We introduce an efficient framework for computing the distance between collider events using the tools of Linearized Optimal Transport (LOT).
