9 citations · 20 across the 12 of their papers we have counts for
Showing 2023 · cs.LGShow all
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cs.LG2023
CROSS-Net: Region-Agnostic Taxi-Demand Prediction Using Feature Disentanglement
Ren Ozeki, Haruki Yonekura, Aidana Baimbetova +2
The growing demand for ride-hailing services has led to an increasing need for accurate taxi demand prediction. Existing systems are limited to specific regions, lacking generality…
cs.LG2023★ 2 cited
Privacy-Preserving Taxi-Demand Prediction Using Federated Learning
Yumeki Goto, Tomoya Matsumoto, Hamada Rizk +2
Taxi-demand prediction is an important application of machine learning that enables taxi-providing facilities to optimize their operations and city planners to improve transportati…