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Faculty of Computing
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By explicitly modeling and constraining human behavior within an epidemic model, SL-BiLEM achieves a remarkable 20x reduction in out-of-distribution performance degradation compared to purely neural approaches when predicting the impact of novel policies.
Robots can now learn flexible, geometry-free interactions with objects directly from video, sidestepping the need for laborious 3D modeling or complex retargeting.
