This repository contains experimentation on selectivity estimation when dealing with spatial filters using optimizer feedback. Explore our experiments and methodologies in selectivity estimation for spatial filters.
Fourier-descriptor features for machine-learned spatial (true-shape) selectivity estimation — code & results for the WISE 2026 paper.
R package: Intuitive niche-breadth estimation in multi-trait and phylogenetic dimensions.
Framework for spatial selectivity estimation using machine learning and optimizer feedback. Addresses both RCC filters and distance-based filters by transforming estimation into regression task. Compares neural networks, tree-based models and instance-based approaches against traditional RTree and histogram methods across 14 spatial datasets.
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