mlsanityData to 7 Oct 2026

Long-term Forecasting with TiDE: Time-series Dense Encoder

arXiv 2304.08424 ↗First posted 17 Apr 2023stat.ML cs.LGcited by 327

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Abstract (arXiv)

Recent work has shown that simple linear models can outperform several Transformer based approaches in long term time-series forecasting. Motivated by this, we propose a Multi-layer Perceptron (MLP) based encoder-decoder model, Time-series Dense Encoder (TiDE), for long-term time-series forecasting that enjoys the simplicity and speed of linear models while also being able to handle covariates and non-linear dependencies. Theoretically, we prove that the simplest linear analogue of our model can achieve near optimal error rate for linear dynamical systems (LDS) under some assumptions. Empirically, we show that our method can match or outperform prior approaches on popular long-term time-series forecasting benchmarks while being 5-10x faster than the best Transformer based model.

Key facts. Cited by 327 papers in the map (data through 7 Oct 2026). Builds on 19 of its 37 references that are in the map. First posted on arXiv 17 Apr 2023.

Builds on

19 of 37 references.

References · 19

  1. 2017Attention Is All You Needcited by 59,932
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2022FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awarenesscited by 3,611
  4. 2021Efficiently Modeling Long Sequences with Structured State Spacescited by 2,424
  5. 2020Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecastingcited by 2,141
  6. 2022A Time Series is Worth 64 Words: Long-term Forecasting with Transformerscited by 1,981
  7. 2021Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecastingcited by 1,654
  8. 2020Linformer: Self-Attention with Linear Complexitycited by 1,462
  9. 2022Are Transformers Effective for Time Series Forecasting?cited by 1,400
  10. 2022FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecastingcited by 1,200
  11. 2017DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networkscited by 1,004
  12. 2019N-BEATS: Neural basis expansion analysis for interpretable time series forecastingcited by 744
7 more
  1. 2019Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecastingcited by 606
  2. 2022Diagonal State Spaces are as Effective as Structured State Spacescited by 350
  3. 2020Coupled Oscillatory Recurrent Neural Network (coRNN): An accurate and (gradient) stable architecture for learning long time dependenciescited by 81
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  5. 2019Deep Independently Recurrent Neural Network (IndRNN)cited by 14
  6. 2021On the benefits of maximum likelihood estimation for Regression and Forecastingcited by 8
  7. 2022Task-Synchronized Recurrent Neural Networkscited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 17; 2024: 105; 2025: 116; 2026: 89.

327 papers.

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  1. 2023iTransformer: Inverted Transformers Are Effective for Time Series Forecastingcited by 906
  2. 2023A decoder-only foundation model for time-series forecastingcited by 650
  3. 2024Unified Training of Universal Time Series Forecasting Transformerscited by 588
  4. 2024Titans: Learning to Memorize at Test Timecited by 303
  5. 2024Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Expertscited by 280
  6. 2024TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methodscited by 242
  7. 2024TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variablescited by 241
  8. 2024Timer: Generative Pre-trained Transformers Are Large Time Series Modelscited by 198
  9. 2024Deep Time Series Models: A Comprehensive Survey and Benchmarkcited by 191
  10. 2024GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluationcited by 188
  11. 2023TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecastingcited by 170
  12. 2025Sundial: A Family of Highly Capable Time Series Foundation Modelscited by 168
38 more
  1. 2024TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysiscited by 113
  2. 2024Is Mamba Effective for Time Series Forecasting?cited by 110
  3. 2024CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuningcited by 105
  4. 2024DUET: Dual Clustering Enhanced Multivariate Time Series Forecastingcited by 104
  5. 2024SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameterscited by 103
  6. 2024Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecastingcited by 102
  7. 2024CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patternscited by 102
  8. 2024UniTS: A Unified Multi-Task Time Series Modelcited by 93
  9. 2024Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Expertscited by 88
  10. 2024SiMBA: Simplified Mamba-Based Architecture for Vision and Multivariate Time seriescited by 81
  11. 2024FreDF: Learning to Forecast in the Frequency Domaincited by 77
  12. 2024SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusioncited by 75
  13. 2024Time-MMD: Multi-Domain Multimodal Dataset for Time Series Analysiscited by 65
  14. 2024AutoTimes: Autoregressive Time Series Forecasters via Large Language Modelscited by 63
  15. 2024TimeMachine: A Time Series is Worth 4 Mambas for Long-term Forecastingcited by 63
  16. 2024Scaling Wearable Foundation Modelscited by 57
  17. 2025This Time is Different: An Observability Perspective on Time Series Foundation Modelscited by 57
  18. 2023CARD: Channel Aligned Robust Blend Transformer for Time Series Forecastingcited by 55
  19. 2023SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecastingcited by 53
  20. 2024Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modelingcited by 44
  21. 2024Toto: Time Series Optimized Transformer for Observabilitycited by 44
  22. 2024Fredformer: Frequency Debiased Transformer for Time Series Forecastingcited by 43
  23. 2024TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecastingcited by 38
  24. 2024TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysiscited by 37
  25. 2024From Similarity to Superiority: Channel Clustering for Time Series Forecastingcited by 37
  26. 2024Adaptive Multi-Scale Decomposition Framework for Time Series Forecastingcited by 34
  27. 2024In-Context Fine-Tuning for Time-Series Foundation Modelscited by 31
  28. 2023Mixture-of-Linear-Experts for Long-term Time Series Forecastingcited by 29
  29. 2025Temporal Query Network for Efficient Multivariate Time Series Forecastingcited by 29
  30. 2024ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysiscited by 26
  31. 2024Zero-shot forecasting of chaotic systemscited by 25
  32. 2025OLinear: A Linear Model for Time Series Forecasting in Orthogonally Transformed Domaincited by 25
  33. 2025Amplifier: Bringing Attention to Neglected Low-Energy Components in Time Series Forecastingcited by 23
  34. 2023PETformer: Long-term Time Series Forecasting via Placeholder-enhanced Transformercited by 22
  35. 2023Large Pre-trained time series models for cross-domain Time series analysis taskscited by 22
  36. 2024RWKV-TS: Beyond Traditional Recurrent Neural Network for Time Series Taskscited by 22
  37. 2025Time-o1: Time-Series Forecasting Needs Transformed Label Alignmentcited by 22
  38. 2023ST-MLP: A Cascaded Spatio-Temporal Linear Framework with Channel-Independence Strategy for Traffic Forecastingcited by 21

50 most cited of 327 All 327 (JSON)