A low-rank fast graph computation plus a dynamic spatio-temporal convolution kernel gives FasterSTS competitive traffic forecasts at a fraction of the compute, though not the universal state-of-the-art the paper claims.
Short-term traffic forecasting: Where we are and where we’re going,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
REJECT 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
FasterSTS: A Faster Spatio-Temporal Synchronous Graph Convolutional Networks for Traffic flow Forecasting
A low-rank fast graph computation plus a dynamic spatio-temporal convolution kernel gives FasterSTS competitive traffic forecasts at a fraction of the compute, though not the universal state-of-the-art the paper claims.