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Whitetree is a Python library for exact Mahalanobis nearest-neighbour search on low-dimensional sensor data, using multiple KD-trees to handle inserts and deletes efficiently without rebuilding. Benchmarks show it significantly outperforms alternatives like sklearn's BallTree and FAISS in dynamic scenarios.
This paper introduces GOEN, a pipeline combining multi-scale features, L2 normalization, and Mahalanobis distance for OOD detection, and finds that CenterLoss regularization actually degrades OOD performance despite improving classification accuracy.