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Found 2 papers, 1 papers with code
DivShift: Exploring Domain-Specific Distribution Shifts in Large-Scale, Volunteer-Collected Biodiversity Datasets
Here we introduce Diversity Shift (DivShift), a framework for quantifying the effects of domain-specific distribution shifts on machine learning model performance.
Contrastive ground-level image and remote sensing pre-training improves representation learning for natural world imagery
Multimodal image-text contrastive learning has shown that joint representations can be learned across modalities.
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