Sample-efficient active learning for materials informatics using integrated posterior variance

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Notice how the highlighted region shrinks at each step. The algorithm never examines points outside the narrowing window. In a balanced tree with nnn points, this takes about log⁡4(n)\log_4(n)log4​(n) steps. For a million points, that's roughly 10 steps instead of a million comparisons.

Why is HMR