mlsanityData to 7 Oct 2026

A Comprehensive Survey of Deep Learning for Multivariate Time Series Forecasting: A Channel Strategy Perspective

arXiv 2502.10721 ↗First posted 15 Feb 2025cs.LGcited by 58

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Abstract (arXiv)

Multivariate Time Series Forecasting (MTSF) plays a crucial role across diverse fields, ranging from economic, energy, to traffic. In recent years, deep learning has demonstrated outstanding performance in MTSF tasks. In MTSF, modeling the correlations among different channels is critical, as leveraging information from other related channels can significantly improve the prediction accuracy of a specific channel. This study systematically reviews the channel modeling strategies for time series and proposes a taxonomy organized into three hierarchical levels: the strategy perspective, the mechanism perspective, and the characteristic perspective. On this basis, we provide a structured analysis of these methods and conduct an in-depth examination of the advantages and limitations of different channel strategies. Finally, we summarize and discuss some future research directions to provide useful research guidance. Moreover, we maintain an up-to-date Github repository (https://github.com/decisionintelligence/CS4TS) which includes all the papers discussed in the survey.

Key facts. Cited by 58 papers in the map (data through 7 Oct 2026). Builds on 37 of its 47 references that are in the map. First posted on arXiv 15 Feb 2025.

Builds on

37 of 47 references.

References · 37

  1. 2020Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecastingcited by 2,141
  2. 2022A Time Series is Worth 64 Words: Long-term Forecasting with Transformerscited by 1,981
  3. 2021Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecastingcited by 1,654
  4. 2022Are Transformers Effective for Time Series Forecasting?cited by 1,400
  5. 2022FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecastingcited by 1,200
  6. 2022TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysiscited by 1,030
  7. 2023iTransformer: Inverted Transformers Are Effective for Time Series Forecastingcited by 906
  8. 2023Time-LLM: Time Series Forecasting by Reprogramming Large Language Modelscited by 680
  9. 2023One Fits All:Power General Time Series Analysis by Pretrained LMcited by 615
  10. 2024Unified Training of Universal Time Series Forecasting Transformerscited by 588
  11. 2020Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networkscited by 563
  12. 2022Transformers in Time Series: A Surveycited by 489
25 more
  1. 2024TimeMixer: Decomposable Multiscale Mixing for Time Series Forecastingcited by 333
  2. 2024TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methodscited by 242
  3. 2024Timer: Generative Pre-trained Transformers Are Large Time Series Modelscited by 198
  4. 2024Deep Time Series Models: A Comprehensive Survey and Benchmarkcited by 191
  5. 2023TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecastingcited by 170
  6. 2021Discrete Graph Structure Learning for Forecasting Multiple Time Seriescited by 169
  7. 2023TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecastingcited by 136
  8. 2023FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspectivecited by 126
  9. 2024Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Seriescited by 120
  10. 2024DUET: Dual Clustering Enhanced Multivariate Time Series Forecastingcited by 104
  11. 2024CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patternscited by 102
  12. 2024SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusioncited by 75
  13. 2025TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecastingcited by 60
  14. 2023CARD: Channel Aligned Robust Blend Transformer for Time Series Forecastingcited by 55
  15. 2023MSGNet: Learning Multi-Scale Inter-Series Correlations for Multivariate Time Series Forecastingcited by 50
  16. 2024From Similarity to Superiority: Channel Clustering for Time Series Forecastingcited by 37
  17. 2022Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series Forecastingcited by 36
  18. 2024Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicatorscited by 32
  19. 2023Fully-Connected Spatial-Temporal Graph for Multivariate Time-Series Datacited by 23
  20. 2024S2IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecastingcited by 17
  21. 2022FECAM: Frequency Enhanced Channel Attention Mechanism for Time Series Forecastingcited by 15
  22. 2024VCformer: Variable Correlation Transformer with Inherent Lagged Correlation for Multivariate Time Series Forecastingcited by 12
  23. 2024Channel-Aware Low-Rank Adaptation in Time Series Forecastingcited by 12
  24. 2024MCformer: Multivariate Time Series Forecasting with Mixed-Channels Transformercited by 10
  25. 2024DGCformer: Deep Graph Clustering Transformer for Multivariate Time Series Forecastingcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 30; 2026: 28.

58 papers.

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  1. 2025TAB: Unified Benchmarking of Time Series Anomaly Detection Methodscited by 58
  2. 2025Rethinking Irregular Time Series Forecasting: A Simple yet Effective Baselinecited by 54
  3. 2025DBLoss: Decomposition-based Loss Function for Time Series Forecastingcited by 44
  4. 2025Patch-wise Structural Loss for Time Series Forecastingcited by 34
  5. 2025Enhancing Time Series Forecasting through Selective Representation Spaces: A Patch Perspectivecited by 34
  6. 2025Aurora: Towards Universal Generative Multimodal Time Series Forecastingcited by 28
  7. 2026TimeART: Towards Agentic Time Series Reasoning via Tool-Augmentationcited by 25
  8. 2025CRISP-SAM2: SAM2 with Cross-Modal Interaction and Semantic Prompting for Multi-Organ Segmentationcited by 12
  9. 2026GCGNet: Graph-Consistent Generative Network for Time Series Forecasting with Exogenous Variablescited by 11
  10. 2025K2VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecastingcited by 7
  11. 2025ASTGI: Adaptive Spatio-Temporal Graph Interactions for Irregular Multivariate Time Series Forecastingcited by 7
  12. 2025AimTS: Augmented Series and Image Contrastive Learning for Time Series Classificationcited by 5
38 more
  1. 2025CoRA: Covariate-Aware Adaptation of Time Series Foundation Modelscited by 5
  2. 2026Decentralized Attention Fails Centralized Signals: Rethinking Transformers for Medical Time Seriescited by 5
  3. 2025Multi-Order Wavelet Derivative Transform for Deep Time Series Forecastingcited by 4
  4. 2025MLLM4TS: Leveraging Vision and Multimodal Language Models for General Time-Series Analysiscited by 4
  5. 2026Unlocking the Value of Text: Event-Driven Reasoning and Multi-Level Alignment for Time Series Forecastingcited by 4
  6. 2025FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecastingcited by 3
  7. 2026Towards Multimodal Time Series Anomaly Detection with Semantic Alignment and Condensed Interactioncited by 3
  8. 2025Task-Aware Mixture-of-Experts for Time Series Analysiscited by 2
  9. 2025Diffusion-Based Image Editing: An Unforeseen Adversary to Robust Invisible Watermarkscited by 2
  10. 2025TARFVAE: Efficient One-Step Generative Time Series Forecasting via TARFLOW based VAEcited by 2
  11. 2026MEMTS: Internalizing Domain Knowledge via Parameterized Memory for Retrieval-Free Domain Adaptation of Time Series Foundation Modelscited by 2
  12. 2026Vanishing Watermarks: Diffusion-Based Image Editing Undermines Robust Invisible Watermarkingcited by 2
  13. 2026Anomalies in Multivariate Time Series Benchmarks Are Mostly Univariatecited by 2
  14. 2025Rating Quality of Diverse Time Series Data by Meta-learning from LLM Judgmentcited by 1
  15. 2025ADFormer: Aggregation Differential Transformer for Passenger Demand Forecastingcited by 1
  16. 2025SEED: Spectral Entropy-Guided Evaluation of SpatialTemporal Dependencies for Multivariate Time Series Forecastingcited by 1
  17. 2026ST-EVO: Towards Generative Spatio-Temporal Evolution of Multi-Agent Communication Topologiescited by 1
  18. 2026Editing on the Generative Manifold: A Theoretical and Empirical Study of General Diffusion-Based Image Editing Trade-offscited by 1
  19. 2026What If We Let Forecasting Forget? A Sparse Bottleneck for Cross-Variable Dependenciescited by 1
  20. 2026L-Drive: Beyond a Single Mapping-Latent Context Drives Time Series Forecastingcited by 1
  21. 2026Multivariate Time Series Forecasting needs Cross Variable Losscited by 1
  22. 2025Segregation and Context Aggregation Network for Real-time Cloud Segmentationcited by 0
  23. 2025Enhancing Channel-Independent Time Series Forecasting via Cross-Variate Patch Embeddingcited by 0
  24. 2025SCAWaveNet: A Spatial-Channel Attention-Based Network for Global Significant Wave Height Retrievalcited by 0
  25. 2025FADE: Adversarial Concept Erasure in Flow Modelscited by 0
  26. 2025PRISM: Lightweight Multivariate Time-Series Classification through Symmetric Multi-Resolution Convolutional Layerscited by 0
  27. 2025Robust Concept Erasure in Diffusion Models: A Theoretical Perspective on Security and Robustnesscited by 0
  28. 2025Dynamic Relational Priming Improves Transformer in Multivariate Time Seriescited by 0
  29. 2025TSGym: Design Choices for Deep Multivariate Time-Series Forecastingcited by 0
  30. 2025InvDec: Inverted Decoder for Multivariate Time Series Forecasting with Separated Temporal and Variate Modelingcited by 0
  31. 2025MSTN: A Lightweight and Fast Model for General TimeSeries Analysiscited by 0
  32. 2026Dual-Prototype Disentanglement: A Context-Aware Enhancement Framework for Time Series Forecastingcited by 0
  33. 2026ASGMamba: Adaptive Spectral Gating Mamba for Multivariate Time Series Forecastingcited by 0
  34. 2026SyncTrack: Rhythmic Stability and Synchronization in Multi-Track Music Generationcited by 0
  35. 2026When Denoising Becomes Unsigning: Theoretical and Empirical Analysis of Watermark Fragility Under Diffusion-Based Image Editingcited by 0
  36. 2026Permutation-Equivariant 2D State Space Models: Theory and Canonical Architecture for Multivariate Time Seriescited by 0
  37. 2026Editing Away the Evidence: Diffusion-Based Image Manipulation and the Failure Modes of Robust Watermarkingcited by 0
  38. 2026Deep Time-Series Forecasting in 10 Years: A Surveycited by 0

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