A gradient flow perspective on the quantization problem
Mikaela Iacobelli

TL;DR
This paper reviews a dynamical approach to measure quantization, analyzing recent results in low dimensions and extending static quantization problems to Riemannian manifolds, offering new insights into the mathematical structure of quantization.
Contribution
It introduces a gradient flow perspective on measure quantization and extends the analysis to arbitrary Riemannian manifolds, providing a unified dynamical framework.
Findings
Analysis of quantization in 1 and 2 dimensions
Extension of static quantization results to Riemannian manifolds
New dynamical approach to measure quantization
Abstract
In this paper we review recent results by the author on the problem of quantization of measures. More precisely, we propose a dynamical approach, and we investigate it in dimensions 1 and 2. Moreover, we discuss a recent general result on the static problem on arbitrary Riemannian manifolds.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
