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continuous normalizing flows

topic1 events
papersTODAY 04:00 UTC

Lagrangian Sub-Flow Method Improves Out-of-Distribution Detection

Researchers propose a Lagrangian sub-flow framework built on continuous normalizing flows to detect out-of-distribution observations that lie in a subspace of high-dimensional data. The approach applies local diagnostics to the flow, aiming to better separate in-distribution samples from anomalous ones. The work is presented as a preprint on arXiv.

ood-detection/normalizing-flows/research/anomaly-detection