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MIND: Monge Inception Distance for Generative Models Evaluation

cs.LG · 2026-05-07 · unverdicted · novelty 5.0

MIND uses sliced Wasserstein distance on Inception features to evaluate generative models, matching FID performance with 10x fewer samples and 100x faster computation while being more robust to moment-matching attacks.

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  • MIND: Monge Inception Distance for Generative Models Evaluation cs.LG · 2026-05-07 · unverdicted · none · ref 32

    MIND uses sliced Wasserstein distance on Inception features to evaluate generative models, matching FID performance with 10x fewer samples and 100x faster computation while being more robust to moment-matching attacks.