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Greatest papers with code

Scalable Low-Rank Autoregressive Tensor Learning for Spatiotemporal Traffic Data Imputation

7 Aug 2020xinychen/awesome-latex-drawing

Recent studies based on tensor nuclear norm have demonstrated the superiority of tensor learning in imputation tasks by effectively characterizing the complex correlations/dependencies in spatiotemporal data.

IMPUTATION TRAFFIC DATA IMPUTATION

A Nonconvex Low-Rank Tensor Completion Model for Spatiotemporal Traffic Data Imputation

23 Mar 2020xinychen/awesome-latex-drawing

Sparsity and missing data problems are very common in spatiotemporal traffic data collected from various sensing systems.

IMPUTATION TRAFFIC DATA IMPUTATION

Low-Rank Autoregressive Tensor Completion for Spatiotemporal Traffic Data Imputation

30 Apr 2021xinychen/transdim

In this paper, we propose a low-rank autoregressive tensor completion (LATC) framework by introducing \textit{temporal variation} as a new regularization term into the completion of a third-order (sensor $\times$ time of day $\times$ day) tensor.

IMPUTATION TIME SERIES TRAFFIC DATA IMPUTATION

Traffic Data Imputation using Deep Convolutional Neural Networks

21 Jan 2020bilzinet/Traffic-state-reconstruction-using-Deep-CNN

We propose a statistical learning-based traffic speed estimation method that uses sparse vehicle trajectory information.

IMPUTATION TRAFFIC DATA IMPUTATION