Robust Traffic Prediction
2 papers with code • 0 benchmarks • 0 datasets
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Most implemented papers
Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction
echo-ji/st-ssl
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ii) These models fail to capture the temporal heterogeneity induced by time-varying traffic patterns, as they typically model temporal correlations with a shared parameterized space for all time periods.
Seeing the Unseen: Learning Basis Confounder Representations for Robust Traffic Prediction
However, the relations of X -> Y are often influenced by external confounders that simultaneously affect both X and Y , such as weather, accidents, and holidays.
