mlsanityData to 14 Oct 2026

Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting

arXiv 2405.10800 ↗First posted 17 May 2024cs.LGcited by 18

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Abstract (arXiv)

Spatiotemporal time series forecasting plays a key role in a wide range of real-world applications. While significant progress has been made in this area, fully capturing and leveraging spatiotemporal heterogeneity remains a fundamental challenge. Therefore, we propose a novel Heterogeneity-Informed Meta-Parameter Learning scheme. Specifically, our approach implicitly captures spatiotemporal heterogeneity through learning spatial and temporal embeddings, which can be viewed as a clustering process. Then, a novel spatiotemporal meta-parameter learning paradigm is proposed to learn spatiotemporal-specific parameters from meta-parameter pools, which is informed by the captured heterogeneity. Based on these ideas, we develop a Heterogeneity-Informed Spatiotemporal Meta-Network (HimNet) for spatiotemporal time series forecasting. Extensive experiments on five widely-used benchmarks demonstrate our method achieves state-of-the-art performance while exhibiting superior interpretability. Our code is available at https://github.com/XDZhelheim/HimNet.

Key facts. Cited by 18 papers in the map (data through 14 Oct 2026). Builds on 34 of its 71 references that are in the map. First posted on arXiv 17 May 2024.

Builds on

34 of 71 references.

References · 34

  1. 2017Attention Is All You Needcited by 60,361
  2. 2014Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelingcited by 2,367
  3. 2020Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecastingcited by 2,169
  4. 2021Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecastingcited by 1,676
  5. 2017Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecastingcited by 1,136
  6. 2016HyperNetworkscited by 1,027
  7. 2017Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networkscited by 879
  8. 2019Graph WaveNet for Deep Spatial-Temporal Graph Modelingcited by 829
  9. 2020Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networkscited by 566
  10. 2020Adaptive Graph Convolutional Recurrent Network for Traffic Forecastingcited by 530
  11. 2022Transformers in Time Series: A Surveycited by 497
  12. 2019GMAN: A Graph Multi-Attention Network for Traffic Predictioncited by 434
22 more
  1. 2016Dynamic Filter Networkscited by 319
  2. 2021Spectral Temporal Graph Neural Network for Multivariate Time-series Forecastingcited by 299
  3. 2020Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecastingcited by 213
  4. 2021Spatial-Temporal Graph ODE Networks for Traffic Flow Forecastingcited by 210
  5. 2021Discrete Graph Structure Learning for Forecasting Multiple Time Seriescited by 171
  6. 2022Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecastingcited by 151
  7. 2023Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysiscited by 117
  8. 2016Learning feed-forward one-shot learnerscited by 93
  9. 2022Spatio-Temporal Meta-Graph Learning for Traffic Forecastingcited by 88
  10. 2022Spatio-Temporal Self-Supervised Learning for Traffic Flow Predictioncited by 77
  11. 2021DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Predictioncited by 73
  12. 2020Coupled Layer-wise Graph Convolution for Transportation Demand Predictioncited by 54
  13. 2023Spatio-temporal Diffusion Point Processescited by 52
  14. 2023Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatmentcited by 47
  15. 2022Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfercited by 43
  16. 2021Historical Inertia: A Neglected but Powerful Baseline for Long Sequence Time-series Forecastingcited by 26
  17. 2021Learning to Remember Patterns: Pattern Matching Memory Networks for Traffic Forecastingcited by 19
  18. 2018Meta Multi-Task Learning for Sequence Modelingcited by 18
  19. 2024TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Expertscited by 18
  20. 2023FRIGATE: Frugal Spatio-temporal Forecasting on Road Networkscited by 14
  21. 2023Robust Spatiotemporal Traffic Forecasting with Reinforced Dynamic Adversarial Trainingcited by 9
  22. 2023Learning Gaussian Mixture Representations for Tensor Time Series Forecastingcited by 6

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 3; 2025: 7; 2026: 8.

18 papers.

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  1. 2024Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Expertscited by 287
  2. 2024Expand and Compress: Exploring Tuning Principles for Continual Spatio-Temporal Graph Forecastingcited by 10
  3. 2025How Different from the Past? Spatio-Temporal Time Series Forecasting with Self-Supervised Deviation Learningcited by 4
  4. 2025A Gravity-informed Spatiotemporal Transformer for Human Activity Intensity Predictioncited by 2
  5. 2026Enhancing Ride-Hailing Forecasting at DiDi with Multi-View Geospatial Representation Learning from the Webcited by 2
  6. 2025Efficient Traffic Forecasting on Large-Scale Road Network by Regularized Adaptive Graph Convolutioncited by 1
  7. 2026Nested Spatio-Temporal Time Series Forecastingcited by 1
  8. 2024HiMoE: Heterogeneity-Informed Mixture-of-Experts for Fair Spatial-Temporal Forecastingcited by 0
  9. 2025Accurate and Efficient Multivariate Time Series Forecasting via Offline Clusteringcited by 0
  10. 2025Proxy Reconstruction Pre-training for Ramp Flow Prediction at Highway Interchangescited by 0
  11. 2025Efficient Linear Attention for Multivariate Time Series Modeling via Entropy Equalitycited by 0
  12. 2025Towards Resilient Transportation: A Conditional Transformer for Accident-Informed Traffic Forecastingcited by 0
6 more
  1. 2026MP3: Multi-Period Pattern Pre-training for Spatio-Temporal Forecastingcited by 0
  2. 2026Behaviour-Conditioned Neural Processes for Adaptive Residential Short-Term Load Forecastingcited by 0
  3. 2026Fourier Geometric Wind Power Forecasting with Numerical Weather Predictioncited by 0
  4. 2026TimeES: Probabilistic and Deterministic Time Series Forecasting via Evolutionary Spectracited by 0
  5. 2026Addressing Spatial Indistinguishability in Spatiotemporal Prediction via Optimal Transport-Guided Maskingcited by 0
  6. 2026AdaST: Adaptive Coupling for Spatial-Temporal Forecastingcited by 0