mlsanityData to 14 Oct 2026

ST-MLP: A Cascaded Spatio-Temporal Linear Framework with Channel-Independence Strategy for Traffic Forecasting

arXiv 2308.07496 ↗First posted 14 Aug 2023cs.LG cs.AIcited by 22

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Abstract (arXiv)

The criticality of prompt and precise traffic forecasting in optimizing traffic flow management in Intelligent Transportation Systems (ITS) has drawn substantial scholarly focus. Spatio-Temporal Graph Neural Networks (STGNNs) have been lauded for their adaptability to road graph structures. Yet, current research on STGNNs architectures often prioritizes complex designs, leading to elevated computational burdens with only minor enhancements in accuracy. To address this issue, we propose ST-MLP, a concise spatio-temporal model solely based on cascaded Multi-Layer Perceptron (MLP) modules and linear layers. Specifically, we incorporate temporal information, spatial information and predefined graph structure with a successful implementation of the channel-independence strategy - an effective technique in time series forecasting. Empirical results demonstrate that ST-MLP outperforms state-of-the-art STGNNs and other models in terms of accuracy and computational efficiency. Our finding encourages further exploration of more concise and effective neural network architectures in the field of traffic forecasting.

Key facts. Cited by 22 papers in the map (data through 14 Oct 2026). Builds on 29 of its 51 references that are in the map. First posted on arXiv 14 Aug 2023.

Builds on

29 of 51 references.

References · 29

  1. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,361
  2. 2020Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecastingcited by 2,169
  3. 2022A Time Series is Worth 64 Words: Long-term Forecasting with Transformerscited by 2,039
  4. 2021Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecastingcited by 1,676
  5. 2021MLP-Mixer: An all-MLP Architecture for Visioncited by 1,446
  6. 2022Are Transformers Effective for Time Series Forecasting?cited by 1,424
  7. 2022FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecastingcited by 1,210
  8. 2017Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecastingcited by 1,136
  9. 2019Graph WaveNet for Deep Spatial-Temporal Graph Modelingcited by 829
  10. 2020Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networkscited by 566
  11. 2020Adaptive Graph Convolutional Recurrent Network for Traffic Forecastingcited by 530
  12. 2019GMAN: A Graph Multi-Attention Network for Traffic Predictioncited by 434
17 more
  1. 2023Long-term Forecasting with TiDE: Time-series Dense Encodercited by 332
  2. 2021Spectral Temporal Graph Neural Network for Multivariate Time-series Forecastingcited by 299
  3. 2023FITS: Modeling Time Series with 10k Parameterscited by 195
  4. 2020Spatial-Temporal Transformer Networks for Traffic Flow Forecastingcited by 180
  5. 2021Discrete Graph Structure Learning for Forecasting Multiple Time Seriescited by 171
  6. 2021Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solutioncited by 157
  7. 2022Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecastingcited by 151
  8. 2023A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detectioncited by 145
  9. 2022Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecastingcited by 123
  10. 2023Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictorscited by 113
  11. 2023The Capacity and Robustness Trade-off: Revisiting the Channel Independent Strategy for Multivariate Time Series Forecastingcited by 101
  12. 2021Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecastingcited by 67
  13. 2020FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecastingcited by 30
  14. 2021Historical Inertia: A Neglected but Powerful Baseline for Long Sequence Time-series Forecastingcited by 26
  15. 2023Do We Really Need Graph Neural Networks for Traffic Forecasting?cited by 20
  16. 2023ST-GIN: An Uncertainty Quantification Approach in Traffic Data Imputation with Spatio-temporal Graph Attention and Bidirectional Recurrent United Neural Networkscited by 8
  17. 2022A K-variate Time Series Is Worth K Words: Evolution of the Vanilla Transformer Architecture for Long-term Multivariate Time Series Forecastingcited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 13; 2025: 5; 2026: 3.

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  1. 2024Foundation Models for Time Series Analysis: A Tutorial and Surveycited by 239
  2. 2024A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challengescited by 90
  3. 2024SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusioncited by 76
  4. 2024TSI-Bench: Benchmarking Time Series Imputationcited by 33
  5. 2023Mixture-of-Linear-Experts for Long-term Time Series Forecastingcited by 29
  6. 2024Unlocking the Power of LSTM for Long Term Time Series Forecastingcited by 29
  7. 2024Large Language Models for Mobility Analysis in Transportation Systems: A Survey on Forecasting Taskscited by 16
  8. 2025Efficient Traffic Prediction Through Spatio-Temporal Distillationcited by 12
  9. 2024Uncertainty-Aware Crime Prediction With Spatial Temporal Multivariate Graph Neural Networkscited by 5
  10. 2025How Different from the Past? Spatio-Temporal Time Series Forecasting with Self-Supervised Deviation Learningcited by 4
  11. 2024Unifying Lane-Level Traffic Prediction from a Graph Structural Perspective: Benchmark and Baselinecited by 3
  12. 2025Fine-Grained Traffic Inference from Road to Lane via Spatio-Temporal Graph Node Generationcited by 3
10 more
  1. 2024Daily Physical Activity Monitoring -- Adaptive Learning from Multi-source Motion Sensor Datacited by 2
  2. 2024PreMixer: MLP-Based Pre-training Enhanced MLP-Mixers for Large-scale Traffic Forecastingcited by 2
  3. 2025A Gravity-informed Spatiotemporal Transformer for Human Activity Intensity Predictioncited by 2
  4. 2024Causal Adjacency Learning for Spatiotemporal Prediction Over Graphscited by 1
  5. 2024Generative Pre-trained Ranking Model with Over-parameterization at Web-Scale (Extended Abstract)cited by 0
  6. 2024APS-LSTM: Exploiting Multi-Periodicity and Diverse Spatial Dependencies for Flood Forecastingcited by 0
  7. 2025Channel-Independent Federated Traffic Predictioncited by 0
  8. 2026DWAFM: Dynamic Weighted Graph Structure Embedding Integrated with Attention and Frequency-Domain MLPs for Traffic Forecastingcited by 0
  9. 2026Decorrelating the Future: Joint Frequency Domain Learning for Spatio-temporal Forecastingcited by 0
  10. 2026Beyond the Graph: An Adaptive Meta-Learner Fuses Explainability, Weather, and Dynamics for Robust Bus ETA Predictioncited by 0