mlsanityData to 13 Oct 2026

Machine Learning Advances for Time Series Forecasting

arXiv 2012.12802 ↗First posted 23 Dec 2020econ.EM cs.LG stat.APcited by 49

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Abstract (arXiv)

In this paper we survey the most recent advances in supervised machine learning and high-dimensional models for time series forecasting. We consider both linear and nonlinear alternatives. Among the linear methods we pay special attention to penalized regressions and ensemble of models. The nonlinear methods considered in the paper include shallow and deep neural networks, in their feed-forward and recurrent versions, and tree-based methods, such as random forests and boosted trees. We also consider ensemble and hybrid models by combining ingredients from different alternatives. Tests for superior predictive ability are briefly reviewed. Finally, we discuss application of machine learning in economics and finance and provide an illustration with high-frequency financial data.

Key facts. Cited by 49 papers in the map (data through 13 Oct 2026). First posted on arXiv 23 Dec 2020.

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Citing papers per year: 2021: 2; 2022: 10; 2023: 12; 2024: 12; 2025: 10; 2026: 3.

49 papers.

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  1. 2024Probabilistic Forecasting with Stochastic Interpolants and F"ollmer Processescited by 64
  2. 2022Koopman Neural Forecaster for Time Series with Temporal Distribution Shiftscited by 35
  3. 2023STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Predictioncited by 35
  4. 2022Review of automated time series forecasting pipelinescited by 17
  5. 2022A preprocessing perspective for quantum machine learning classification advantage using NISQ algorithmscited by 7
  6. 2023Feature Programming for Multivariate Time Series Predictioncited by 7
  7. 2022DeepVol: Volatility Forecasting from High-Frequency Data with Dilated Causal Convolutionscited by 6
  8. 2021The Age of Correlated Features in Supervised Learning based Forecastingcited by 5
  9. 2023Differential Convolutional Fuzzy Time Series Forecastingcited by 5
  10. 2024Assessing the Impact of Distribution Shift on Reinforcement Learning Performancecited by 4
  11. 2025The Impact of Feature Scaling In Machine Learning: Effects on Regression and Classification Taskscited by 4
  12. 2022Review of Time Series Forecasting Methods and Their Applications to Particle Acceleratorscited by 3
37 more
  1. 2023DeepTSF: Codeless machine learning operations for time series forecastingcited by 3
  2. 2024Conditional Denoising Meets Polynomial Modeling: A Flexible Decoupled Framework for Time Series Forecastingcited by 3
  3. 2024Stabilizing black-box model selection with the inflated argmaxcited by 3
  4. 2024Stratify: Unifying Multi-Step Forecasting Strategiescited by 3
  5. 2023A Survey on Event Prediction Methods from a Systems Perspective: Bringing Together Disparate Research Areascited by 2
  6. 2023Multivariate Time Series characterization and forecasting of VoIP traffic in real mobile networkscited by 2
  7. 2024Learning Low-dimensional Latent Dynamics from High-dimensional Observations: Non-asymptotics and Lower Boundscited by 2
  8. 2024Semiparametric inference for impulse response functions using double/debiased machine learningcited by 2
  9. 2026From Causal Discovery to Dynamic Causal Inference in Neural Time Seriescited by 2
  10. 2022A general framework for multi-step ahead adaptive conformal heteroscedastic time series forecastingcited by 1
  11. 2022Temporal Saliency Detection Towards Explainable Transformer-based Timeseries Forecastingcited by 1
  12. 2023Concentration inequalities for high-dimensional linear processes with dependent innovationscited by 1
  13. 2023A Comprehensive Study of Groundbreaking Machine Learning Research: Analyzing highly cited and impactful publications across six decadescited by 1
  14. 2023Econometrics of Machine Learning Methods in Economic Forecastingcited by 1
  15. 2023auto-sktime: Automated Time Series Forecastingcited by 1
  16. 2024Machine learning and economic forecasting: the role of international trade networkscited by 1
  17. 2024Predicting Company Growth using Scaling Theory informed Machine Learningcited by 1
  18. 2024Time-Series Forecasting in Smart Manufacturing Systems: An Experimental Evaluation of the State-of-the-art Algorithmscited by 1
  19. 2025Exploring Neural Granger Causality with xLSTMs: Unveiling Temporal Dependencies in Complex Datacited by 1
  20. 2025FinTSBridge: A New Evaluation Suite for Real-world Financial Prediction with Advanced Time Series Modelscited by 1
  21. 2025A Contrastive Diffusion-based Network (CDNet) for Time Series Classificationcited by 1
  22. 2021Solving Multistage Stochastic Linear Programming via Regularized Linear Decision Rules: An Application to Hydrothermal Dispatch Planningcited by 0
  23. 2022Improved Batching Strategy For Irregular Time-Series ODEcited by 0
  24. 2022Koopman-theoretic Approach for Identification of Exogenous Anomalies in Nonstationary Time-series Datacited by 0
  25. 2022A Comparative Study of Machine Learning and Deep Learning Techniques for Prediction of Co2 Emission in Carscited by 0
  26. 2023Machine Learning-Assisted Pattern Recognition Algorithms for Estimating Ultimate Tensile Strength in Fused Deposition Modeled Polylactic Acid Specimenscited by 0
  27. 2023Unraveling the Complexity of Splitting Sequential Data: Tackling Challenges in Video and Time Series Analysiscited by 0
  28. 2024Transformers with Attentive Federated Aggregation for Time Series Stock Forecastingcited by 0
  29. 2024Revisiting the Efficacy of Signal Decomposition in AI-based Time Series Predictioncited by 0
  30. 2025Analyzing Patient Daily Movement Behavior Dynamics Using Two-Stage Encoding Modelcited by 0
  31. 2025ML-Based Bidding Price Prediction for Pay-As-Bid Ancillary Services Markets: A Use Case in the German Control Reserve Marketcited by 0
  32. 2025W4S4: WaLRUS Meets S4 for Long-Range Sequence Modelingcited by 0
  33. 2025TSGym: Design Choices for Deep Multivariate Time-Series Forecastingcited by 0
  34. 2025Fighter: Unveiling the Graph Convolutional Nature of Transformers in Time Series Modelingcited by 0
  35. 2025EMTSF:Extraordinary Mixture of SOTA Models for Time Series Forecastingcited by 0
  36. 2026Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecastingcited by 0
  37. 2026Quantum-classical hybrid models based on error correction for time series forecastingcited by 0