mlsanityData to 7 Oct 2026

DSformer: A Double Sampling Transformer for Multivariate Time Series Long-term Prediction

arXiv 2308.03274 ↗First posted 7 Aug 2023cs.LGcited by 49

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Abstract (arXiv)

Multivariate time series long-term prediction, which aims to predict the change of data in a long time, can provide references for decision-making. Although transformer-based models have made progress in this field, they usually do not make full use of three features of multivariate time series: global information, local information, and variables correlation. To effectively mine the above three features and establish a high-precision prediction model, we propose a double sampling transformer (DSformer), which consists of the double sampling (DS) block and the temporal variable attention (TVA) block. Firstly, the DS block employs down sampling and piecewise sampling to transform the original series into feature vectors that focus on global information and local information respectively. Then, TVA block uses temporal attention and variable attention to mine these feature vectors from different dimensions and extract key information. Finally, based on a parallel structure, DSformer uses multiple TVA blocks to mine and integrate different features obtained from DS blocks respectively. The integrated feature information is passed to the generative decoder based on a multi-layer perceptron to realize multivariate time series long-term prediction. Experimental results on nine real-world datasets show that DSformer can outperform eight existing baselines.

Key facts. Cited by 49 papers in the map (data through 7 Oct 2026). Builds on 26 of its 52 references that are in the map. First posted on arXiv 7 Aug 2023.

Builds on

26 of 52 references.

References · 26

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2020Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecastingcited by 2,141
  3. 2022A Time Series is Worth 64 Words: Long-term Forecasting with Transformerscited by 1,981
  4. 2020Reformer: The Efficient Transformercited by 1,658
  5. 2021Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecastingcited by 1,654
  6. 2022Are Transformers Effective for Time Series Forecasting?cited by 1,400
  7. 2022FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecastingcited by 1,200
  8. 2022TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysiscited by 1,030
  9. 2017Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networkscited by 869
  10. 2019Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecastingcited by 606
  11. 2021TS2Vec: Towards Universal Representation of Time Seriescited by 463
  12. 2020A Transformer-based Framework for Multivariate Time Series Representation Learningcited by 449
14 more
  1. 2022Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structurescited by 158
  2. 2022Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecastingcited by 149
  3. 2022FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecastingcited by 147
  4. 2021Graph Neural Controlled Differential Equations for Traffic Forecastingcited by 133
  5. 2022Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecastingcited by 122
  6. 2022Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecastingcited by 117
  7. 2022Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting--Full Versioncited by 59
  8. 2021AutoCTS: Automated Correlated Time Series Forecasting -- Extended Versioncited by 48
  9. 2022Knowledge Graph Contrastive Learning Based on Relation-Symmetrical Structurecited by 43
  10. 2022First De-Trend then Attend: Rethinking Attention for Time-Series Forecastingcited by 19
  11. 2023HUTFormer: Hierarchical U-Net Transformer for Long-Term Traffic Forecastingcited by 12
  12. 2023Message Intercommunication for Inductive Relation Reasoningcited by 8
  13. 2023Compressed Interaction Graph based Framework for Multi-behavior Recommendationcited by 4
  14. 2022SciTS: A Benchmark for Time-Series Databases in Scientific Experiments and Industrial Internet of Thingscited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 19; 2025: 22; 2026: 6.

49 papers.

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  1. 2023Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysiscited by 113
  2. 2024DUET: Dual Clustering Enhanced Multivariate Time Series Forecastingcited by 104
  3. 2024CATCH: Channel-Aware multivariate Time Series Anomaly Detection via Frequency Patchingcited by 91
  4. 2025TAB: Unified Benchmarking of Time Series Anomaly Detection Methodscited by 58
  5. 2025Patch-wise Structural Loss for Time Series Forecastingcited by 34
  6. 2025Aurora: Towards Universal Generative Multimodal Time Series Forecastingcited by 28
  7. 2024Hierarchical Classification Auxiliary Network for Time Series Forecastingcited by 26
  8. 2025LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimizationcited by 21
  9. 2024GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missingcited by 20
  10. 2025Merlin: Multi-View Representation Learning for Robust Multivariate Time Series Forecasting with Unfixed Missing Ratescited by 19
  11. 2024Parametric Augmentation for Time Series Contrastive Learningcited by 12
  12. 2024VCformer: Variable Correlation Transformer with Inherent Lagged Correlation for Multivariate Time Series Forecastingcited by 12
37 more
  1. 2025TimeMosaic: Temporal Heterogeneity Guided Time Series Forecasting via Adaptive Granularity Patch and Segment-wise Decodingcited by 12
  2. 2023Dynamic Frequency Domain Graph Convolutional Network for Traffic Forecastingcited by 10
  3. 2025Selective Learning for Deep Time Series Forecastingcited by 8
  4. 2024On the Integration of Spatial-Temporal Knowledge: A Lightweight Approach to Atmospheric Time Series Forecastingcited by 7
  5. 2025K2VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecastingcited by 7
  6. 2025DualSG: A Dual-Stream Explicit Semantic-Guided Multivariate Time Series Forecasting Frameworkcited by 7
  7. 2024Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecastingcited by 6
  8. 2024XXLTraffic: Expanding and Extremely Long Traffic forecasting beyond test adaptationcited by 6
  9. 2025ReFocus: Reinforcing Mid-Frequency and Key-Frequency Modeling for Multivariate Time Series Forecastingcited by 5
  10. 2025Not All Data are Good Labels: On the Self-supervised Labeling for Time Series Forecastingcited by 4
  11. 2025STA-GANN: A Valid and Generalizable Spatio-Temporal Kriging Approachcited by 4
  12. 2025Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamicscited by 4
  13. 2024DGCformer: Deep Graph Clustering Transformer for Multivariate Time Series Forecastingcited by 3
  14. 2024Scalable Transformer for High Dimensional Multivariate Time Series Forecastingcited by 3
  15. 2024Transfer Learning with Foundational Models for Time Series Forecasting using Low-Rank Adaptationscited by 3
  16. 2025FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecastingcited by 3
  17. 2024Online Policy Distillation with Decision-Attentioncited by 2
  18. 2024Partial-Multivariate Model for Forecastingcited by 2
  19. 2026Zeus: Towards Tuning-Free Foundation Model for Time Series Analysiscited by 2
  20. 2024Understanding Token-level Topological Structures in Transformer-based Time Series Forecastingcited by 1
  21. 2024TwinS: Revisiting Non-Stationarity in Multivariate Time Series Forecastingcited by 1
  22. 2024TiVaT: A Transformer with a Single Unified Mechanism for Capturing Asynchronous Dependencies in Multivariate Time Series Forecastingcited by 1
  23. 2024TEAFormers: TEnsor-Augmented Transformers for Multi-Dimensional Time Series Forecastingcited by 1
  24. 2025Towards Robust Real-World Multivariate Time Series Forecasting: A Unified Framework for Dependency, Asynchrony, and Missingnesscited by 1
  25. 2025DLGAN : Time Series Synthesis Based on Dual-Layer Generative Adversarial Networkscited by 1
  26. 2025ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecastingcited by 1
  27. 2026Fast Mining and Dynamic Time-to-Event Prediction over Multi-sensor Data Streamscited by 1
  28. 2026Towards Trustworthy Report Generation: A Deep Research Agent with Progressive Confidence Estimation and Calibrationcited by 1
  29. 2026From XXLTraffic to EvoXXLTraffic: Scaling Traffic Forecasting to Sensor-Evolving Networkscited by 1
  30. 2024VN-Net: Vision-Numerical Fusion Graph Convolutional Network for Sparse Spatio-Temporal Meteorological Forecastingcited by 0
  31. 2025Fewer yet critical: Reducing Redundant Token Dependencies for Transformer-based Time Series Forecastingcited by 0
  32. 2025Forecast-Then-Optimize Deep Learning Methodscited by 0
  33. 2025C3DE: Causal-Aware Collaborative Neural Controlled Differential Equation for Long-Term Urban Crowd Flow Predictioncited by 0
  34. 2025InvDec: Inverted Decoder for Multivariate Time Series Forecasting with Separated Temporal and Variate Modelingcited by 0
  35. 2025Spatio-temporal Multivariate Time Series Forecast with Chosen Variablescited by 0
  36. 2026Physics Encoded Spatial and Temporal Generative Adversarial Network for Tropical Cyclone Image Super-resolutioncited by 0
  37. 2026ChaosNetBench: Benchmarking Spatio-Temporal Graph Neural Networks on Chaotic Lattice Dynamicscited by 0