1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.LG2025★ 1 cited
Spatio-Temporal Graph Neural Network for Urban Spaces: Interpolating Citywide Traffic Volume
Silke K. Kaiser, Filipe Rodrigues, Carlos Lima Azevedo +1
Graph Neural Networks have shown strong performance in traffic volume forecasting, particularly on highways and major arterial networks. Applying them to urban settings, however, p…
cs.CY2024
From Counting Stations to City-Wide Estimates: Data-Driven Bicycle Volume Extrapolation
Silke K. Kaiser, Nadja Klein, Lynn H. Kaack
Shifting to cycling in urban areas reduces greenhouse gas emissions and improves public health. Street-level bicycle volume information would aid cities in planning targeted infras…