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University of Wisconsin-Madison
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Machine-learning predictors can mislead design decisions, with over 22% of configurations showing unexpected performance reversals that traditional simulation still captures best.
Transforming video generation from a pixel sampling problem to a structured orchestration of the physical world, WNM enables unprecedented control and efficiency in content creation.
PLAG transforms tabular anomaly detection by leveraging pseudo-labels to uncover fine-grained, localized anomalies, outperforming traditional methods that struggle with label scarcity.