# Dynamic grain models via fast heuristics for diagram representations

arXiv: https://arxiv.org/abs/2204.06430 · HTML: https://mlsanity.com/paper/2204.06430/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Apr 2022.

## Built on by (most cited first, 2 of 2)

- [Fitting Generalized Power Diagrams to 3D Image Data: A Prerequisite for Virtual Materials Testing](https://mlsanity.com/paper/2507.14268/) (2025)
- [Superpixel-Based Image Segmentation Using Squared 2-Wasserstein Distances](https://mlsanity.com/paper/2601.17071/) (2026)

## Abstract (arXiv)

The present paper introduces a mathematical model for studying dynamic grain growth. In particular, we show how characteristic measurements, grain volumes, centroids, and central second-order moments at discrete moments in time can be turned quickly into a continuous description of the grain growth process in terms of geometric diagrams (which largely generalize the well-known Voronoi and Laguerre tessellations). We evaluate the computational behavior of our algorithm on real-world data.