Tag
PyroAdapt proposes a pretrain-retrieve-rank framework to adapt wildfire prediction models for spatial heterogeneity and temporal distribution shifts, improving detection accuracy and prioritizing fire-prone locations under budget constraints.
This paper proposes Gen-ROTDA, a robust optimal transport-guided residual domain adaptation framework for predicting bike-sharing demand under temporal domain shift, achieving improved stability and accuracy compared to baselines, especially with noisy target data.