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HerALD (High-fidelity Exemplar Retrieval with Adaptive Landmark Distillation with Adaptive Landmark Distillation), a gradient-free graph condensation framework that adapts the node scoring and feature selection in the condensation pipeline to the graph's measured heterophily, is proposed.
Shifting latent space embeddings towards higher density regions with Mean Shift Density Enhancement unlocks near-perfect anomaly detection in medical images, even with limited training data.
