| PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series | May 30, 2023 | Anomaly DetectionClassification | CodeCode Available | 2 | 5 |
| Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse Observations | May 26, 2022 | ImputationMultivariate Time Series Imputation | CodeCode Available | 1 | 5 |
| Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks | Jul 31, 2021 | Graph Neural NetworkImputation | CodeCode Available | 1 | 5 |
| Truncated tensor Schatten p-norm based approach for spatiotemporal traffic data imputation with complicated missing patterns | May 19, 2022 | Cloud ComputingImputation | CodeCode Available | 1 | 5 |
| DiffLight: A Partial Rewards Conditioned Diffusion Model for Traffic Signal Control with Missing Data | Oct 30, 2024 | Decision MakingImputation | CodeCode Available | 1 | 5 |
| Traffic Data Imputation using Deep Convolutional Neural Networks | Jan 21, 2020 | DecoderImputation | CodeCode Available | 1 | 5 |
| Traffic state data imputation: An efficient generating method based on the graph aggregator | Aug 12, 2022 | Generative Adversarial NetworkImputation | CodeCode Available | 1 | 5 |
| STAMImputer: Spatio-Temporal Attention MoE for Traffic Data Imputation | Jun 9, 2025 | Graph AttentionImputation | CodeCode Available | 0 | 5 |
| Large-Scale Traffic Data Imputation with Spatiotemporal Semantic Understanding | Jan 27, 2023 | ImputationTraffic Data Imputation | CodeCode Available | 0 | 5 |
| An Experimental Evaluation of Imputation Models for Spatial-Temporal Traffic Data | Dec 6, 2024 | BenchmarkingImputation | CodeCode Available | 0 | 5 |
