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Found 2 papers, 1 papers with code
Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning
Large, pretrained models are commonly finetuned with imagery that is heavily augmented to mimic different conditions and scales, with the resulting models used for various tasks with imagery from a range of spatial scales.
Offline Contextual Bandits with High Probability Fairness Guarantees
We present RobinHood, an offline contextual bandit algorithm designed to satisfy a broad family of fairness constraints.
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