Voronoi Tessellation
Voronoi tessellation, a method for partitioning space into regions based on proximity to a set of points, is finding increasing application across diverse scientific fields. Current research focuses on leveraging Voronoi diagrams within machine learning models, particularly convolutional neural networks and other deep learning architectures, to address challenges in spatial data processing, such as sparse field reconstruction, 3D modeling, and multi-agent navigation. These advancements improve efficiency and accuracy in areas ranging from robotics and fluid dynamics simulations to protein structure analysis and genetic variant representation, demonstrating the broad utility of this geometric technique.
Papers
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