Heterogeneity-guided tensor decomposition for traffic flow imputation(Hg-TD)

We propose a heterogeneity-guided tensor decomposition method (Hg-TD) that effectively captures spatiotemporal heterogeneity even in scenarios with missing data and leverages this representation to guide the tensor decomposition process, thereby enhancing the accuracy and robustness of traffic flow imputation.