mlsanityData to 7 Oct 2026

MegaCRN: Meta-Graph Convolutional Recurrent Network for Spatio-Temporal Modeling

arXiv 2212.05989 ↗First posted 12 Dec 2022cs.LG cs.AIcited by 3

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Abstract (arXiv)

Spatio-temporal modeling as a canonical task of multivariate time series forecasting has been a significant research topic in AI community. To address the underlying heterogeneity and non-stationarity implied in the graph streams, in this study, we propose Spatio-Temporal Meta-Graph Learning as a novel Graph Structure Learning mechanism on spatio-temporal data. Specifically, we implement this idea into Meta-Graph Convolutional Recurrent Network (MegaCRN) by plugging the Meta-Graph Learner powered by a Meta-Node Bank into GCRN encoder-decoder. We conduct a comprehensive evaluation on two benchmark datasets (METR-LA and PEMS-BAY) and a large-scale spatio-temporal dataset that contains a variaty of non-stationary phenomena. Our model outperformed the state-of-the-arts to a large degree on all three datasets (over 27% MAE and 34% RMSE). Besides, through a series of qualitative evaluations, we demonstrate that our model can explicitly disentangle locations and time slots with different patterns and be robustly adaptive to different anomalous situations. Codes and datasets are available at https://github.com/deepkashiwa20/MegaCRN.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 41 of its 67 references that are in the map. First posted on arXiv 12 Dec 2022.

Builds on

41 of 67 references.

References · 41

  1. 2017Attention Is All You Needcited by 59,932
  2. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  3. 2017Graph Attention Networkscited by 8,854
  4. 2014Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelingcited by 2,341
  5. 2016Matching Networks for One Shot Learningcited by 2,246
  6. 2020Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecastingcited by 2,141
  7. 2016Convolutional Neural Networks on Graphs with Fast Localized Spectral Filteringcited by 2,085
  8. 2016WaveNet: A Generative Model for Raw Audiocited by 1,710
  9. 2021Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecastingcited by 1,654
  10. 2015Multi-Scale Context Aggregation by Dilated Convolutionscited by 1,128
  11. 2017Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecastingcited by 1,125
  12. 2016HyperNetworkscited by 1,003
29 more
  1. 2017Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networkscited by 869
  2. 2019Graph WaveNet for Deep Spatial-Temporal Graph Modelingcited by 820
  3. 2019Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecastingcited by 606
  4. 2020Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networkscited by 563
  5. 2019Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detectioncited by 560
  6. 2020Adaptive Graph Convolutional Recurrent Network for Traffic Forecastingcited by 525
  7. 2019GMAN: A Graph Multi-Attention Network for Traffic Predictioncited by 433
  8. 2018T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Predictioncited by 399
  9. 2018Neural Relational Inference for Interacting Systemscited by 339
  10. 2021Spectral Temporal Graph Neural Network for Multivariate Time-series Forecastingcited by 298
  11. 2020Learning Memory-guided Normality for Anomaly Detectioncited by 278
  12. 2016Structured Sequence Modeling with Graph Convolutional Recurrent Networkscited by 273
  13. 2021Graph Neural Network for Traffic Forecasting: A Surveycited by 260
  14. 2020Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecastingcited by 212
  15. 2021Spatial-Temporal Graph ODE Networks for Traffic Flow Forecastingcited by 209
  16. 2020Spatial-Temporal Transformer Networks for Traffic Flow Forecastingcited by 179
  17. 2021Discrete Graph Structure Learning for Forecasting Multiple Time Seriescited by 169
  18. 2021Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solutioncited by 156
  19. 2018Temporal Pattern Attention for Multivariate Time Series Forecastingcited by 125
  20. 2021DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Predictioncited by 73
  21. 2021Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecastingcited by 67
  22. 2019Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Predictioncited by 64
  23. 2022Towards Spatio-Temporal Aware Traffic Time Series Forecasting--Full Versioncited by 59
  24. 2020Coupled Layer-wise Graph Convolution for Transportation Demand Predictioncited by 54
  25. 2021Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Networkcited by 52
  26. 2020DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networkscited by 34
  27. 2021A Multi-view Multi-task Learning Framework for Multi-variate Time Series Forecastingcited by 21
  28. 2021Learning to Remember Patterns: Pattern Matching Memory Networks for Traffic Forecastingcited by 19
  29. 2021Event-Aware Multimodal Mobility Nowcastingcited by 18

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 0; 2025: 0; 2026: 1.

3 papers.

  1. 2023WeatherGNN: Exploiting Meteo- and Spatial-Dependencies for Local Numerical Weather Prediction Bias-Correctioncited by 13
  2. 2023Transport-Hub-Aware Spatial-Temporal Adaptive Graph Transformer for Traffic Flow Predictioncited by 0
  3. 2026GEnSHIN: Graphical Enhanced Spatio-temporal Hierarchical Inference Network for Traffic Flow Predictioncited by 0