Time Series Forecasting

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Overview

Time series forecasting studies how to predict future observations from past values, often across multiple horizons and with missing data, changing regimes, or external drivers such as weather and events. Methods range from classical autoregressive and exponential-smoothing models to recurrent networks, Transformers, state-space models, decomposition and frequency-based approaches, graph models, and pretrained foundation models; probabilistic methods also estimate uncertainty. Current work increasingly combines historical patterns with covariates, retrieval, domain knowledge, and online adaptation, while targeting applications from energy and weather to health, transport, and finance. A central tension is that larger or more complex models do not reliably beat simple baselines, and benchmark accuracy may not reflect robustness, forecast structure, uncertainty calibration, or downstream decision value.

Latest papers

CardsList

884 papers113 papers in the last four weeks, down 19% on the four weeks before. 0.7% of all new papers.

  1. A Comparative Study of Machine Learning Models for Hourly Forecasting of Air Temperature and Relative Humidity

    Mar 24, 2026Jiaqi DongWeather ForecastingTime Series Forecasting

  2. Cluster-Specific Predictive Modeling: A Scalable Solution for Resource-Constrained Wi-Fi Controllers

    Mar 23, 2026Gianluca Fontanesi, Luca Barbieri, Lorenzo Galati Giordano +2Time Series ForecastingModel Selection

    Radio Systems Research, Nokia Bell Labs, Stuttgart, Germany · Nokia Spain, Madrid

  3. FISformer: Replacing Self-Attention with a Fuzzy Inference System in Transformer Models for Time Series Forecasting

    Mar 23, 2026Bulent Haznedar, Levent KaracanTime Series TransformersTime Series Forecasting

    Computer Engineering Department, Gaziantep University, Gaziantep, Türkiye

  4. Rethinking Multimodal Fusion for Time Series: Text Modalities Need Constrained Fusion

    Mar 23, 2026Seunghan Lee, Jun Seo, Jaehoon Lee +7Cross-Modal LearningTime Series Forecasting

    LG AI Research Seoul, South Korea

  5. Benchmarking Scientific Machine Learning Models for Air Quality Data

    Mar 22, 2026Khawja Imran Masud, Venkata Sai Rahul Unnam, Sahara AliAir Quality PredictionForecasting Benchmarks

    University of North Texas, 76205 Texas, USA

  6. Long-Term Outlier Prediction Through Outlier Score Modeling

    Mar 22, 2026Yuma Aoki, Joon Park, Koh Takeuchi +6Time-Series Anomaly DetectionUnsupervised Anomaly Detection

    Nara Institute of Science and Technology · Kyoto University · Panasonic Holdings Corporation

  7. ReLaMix: Residual Latency-Aware Mixing for Delay-Robust Financial Time-Series Forecasting

    Mar 21, 2026Tianyou Lai, Wentao Yue, Jiayi Zhou +5Robust Time Series ForecastingTime Series Forecasting

    Lanzhou University, Lanzhou, China · Brandeis University, Waltham, USA · Shenzhen University, Shenzhen, China +2

  8. Centrality-Based Pruning for Efficient Echo State Networks

    Mar 21, 2026Sudip LaudariReservoir ComputingNeural Network Pruning

    Independent Researcher.

  9. Trojan horse hunt in deep forecasting models: Insights from the European Space Agency competition

    Mar 20, 2026Krzysztof Kotowski, Ramez Shendy, Jakub Nalepa +10Backdoor DetectionTime Series Forecasting

    KP Labs, Bojkowska 37J, Gliwice, 44-100, Poland · Silesian University of Technology, Akademicka 16, Gliwice, 44-100, Poland · Warsaw University of Technology, Centre of Credible AI, Pl. Politechniki 1, Warsaw, 00-661, Poland +3

  10. Fine-tuning Timeseries Predictors Using Reinforcement Learning

    Mar 20, 2026Hugo Cazaux, Ralph Rudd, Hlynur Stefánsson +2RL Fine-TuningTime Series Forecasting

    Reykjavik University, Department of Engineering, Menntavegur 1, Reykjavik, 102, Iceland

  11. Deep Time-Series Forecasting in 10 Years: A Survey

    Mar 20, 2026Hao Wang, Licheng Pan, Qingsong Wen +12Time Series Forecasting

    School of Intelligence Science and Technology, Peking University, Beijing 100871, China · School of Cyber Science and Technology, Zhejiang University, Hangzhou, Zhejiang 310027, China · Squirrel AI Learning, Bellevue, WA 98004, USA +7

  12. Rolling-Origin Validation Reverses Model Rankings in Multi-Step PM10 Forecasting: XGBoost, SARIMA, and Persistence

    Mar 19, 2026Federico Garcia Crespi, Eduardo Yubero Funes, Marina Alfosea SimonTime Series ForecastingAir Quality Prediction

    Departamento de Ingeniería de Computadores, Universidad Miguel Hernández, Elche, Spain · Departamento de Física Aplicada, Universidad Miguel Hernández, Elche, Spain

  13. Extending SSMs with the Exponentially Weighted Signature

    Mar 19, 2026Alexandre Bloch, Benjamin Walker, Joël Mouterde +3Dynamical SystemsTime Series Classification

    Mathematical Institute, University of Oxford · SKF · Department of Mathematics, Imperial College London

  14. Adaptive Regime-Aware Stock Price Prediction Using Autoencoder-Gated Dual Node Transformers with Reinforcement Learning Control

    Mar 19, 2026Mohammad Al Ridhawi, Mahtab Haj Ali, Hussein Al OsmanTime Series ForecastingFinance

    School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Canada

  15. MLOW: Interpretable Low-Rank Frequency Magnitude Decomposition of Multiple Effects for Time Series Forecasting

    Mar 19, 2026Runze Yang, Longbing Cao, Xiaoming Wu +4Frequency-Domain Time Series ModelingTime Series Forecasting

    1Macquarie University · 2Shanghai Jiao Tong University · 3Nanyang Technological University +1

  16. Baguan-TS: A Sequence-Native In-Context Learning Model for Time Series Forecasting with Covariates

    Mar 18, 2026Linxiao Yang, Xue Jiang, Gezheng Xu +9Time Series ForecastingMultivariate Time Series Forecasting

    DAMO Academy, Alibaba Group, Hangzhou, China

  17. The Phasor Transformer: Resolving Attention Bottlenecks on the Unit Circle

    Mar 18, 2026Dibakar SigdelTransformerTime Series Forecasting

    Mindverse Computing LLC, WA 98087

  18. Beyond Accuracy: Evaluating Forecasting Models by Multi-Echelon Inventory Cost

    Mar 17, 2026Swata Marik, Swayamjit Saha, Garga ChatterjeeInventory ControlTime Series Forecasting

    Department of Home Science, University of Calcutta, 20 E, Judges Court Road, Alipore, Kolkata, 700027, West Bengal, India. · Department of Computer Science and Engineering, Mississippi State University, 665 George Perry Street, Starkville, 39759, MS, USA. · Psychology Research Unit, Indian Statistical Institute Kolkata, 203, B.T. Road, Kolkata, 700108, West Bengal, India.

  19. Integrating Inductive Biases in Transformers via Distillation for Financial Time Series Forecasting

    Mar 17, 2026Yu-Chen Den, Kuan-Yu Chen, Kendro Vincent +1Time Series ForecastingFinancial Time Series

    SinoPac Holdings, Taipei, Taiwan · National Chengchi University, Taipei, Taiwan

  20. msData: A Millisecond-Resolution Network Dataset for Advancing Time Series Foundation Models

    Mar 17, 2026Subina Khanal, Seshu Tirupathi, Merim Dzaferagic +2Wireless Local Area NetworksTime-Series Foundation Models

    Department of Computer Science Aalborg University · IBM Research, Ireland · Trinity College Dublin

  21. Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables

    Mar 16, 2026Andres Potapczynski, Ravi Kiran Selvam, Tatiana Konstantinova +7Exogenous Time Series ForecastingTime Series Forecasting

    Amazon Science, New York University · Amazon Science

  22. Seeking SOTA: Time-Series Forecasting Must Adopt Taxonomy-Specific Evaluation to Dispel Illusory Gains

    Mar 16, 2026Raeid Saqur, Christoph Bergmeir, Blanka Horvath +3Time Series ForecastingTime Series Modeling

    Dept. of Computer Science, University of Toronto · Dept. of Mathematics, University of Oxford · Vector Institute +5

  23. Unlocking the Value of Text: Event-Driven Reasoning and Multi-Level Alignment for Time Series Forecasting

    Mar 16, 2026Siyuan Wang, Peng Chen, Yihang Wang +4Time Series ForecastingLLM-Based Time Series Forecasting

    East China Normal University

  24. Integrating Weather Foundation Model and Satellite to Enable Fine-Grained Solar Irradiance Forecasting

    Mar 16, 2026Ziqing Ma, Kai Ying, Xinyue Gu +7Solar Irradiance ForecastingSolar Power Forecasting

    DAMO Academy, Alibaba Group, Hangzhou, Zhejiang, China · College of Computer Science, Zhejiang University of Technology, Hangzhou, Zhejiang, China · DAMO Academy, Alibaba Group, Bellevue, USA

  25. GARCH-FIS: A Hybrid Forecasting Model with Dynamic Volatility-Driven Parameter Adaptation

    Mar 16, 2026Wen-Jing Li, Da-Qing ZhangTime Series ForecastingFinancial Time Series

    School of Science, University of Science and Technology Liaoning, Anshan, Liaoning Province, 114051, PR China

  26. Not All Retrievals are Useful: Cross-Attention for Input-Aware RAG in Time Series Forecasting

    Mar 16, 2026Seunghan Lee, Jaehoon Lee, Jun Seo +7Zero-Shot Time Series ForecastingCross-Attention

    LG AI Research Seoul, South Korea

  27. Gated Graph Attention Networks for Predicting Duration of Large Scale Power Outages Induced by Natural Disasters

    Mar 14, 2026Chenghao Duan, Chuanyi Ji, Anwar Walid +1Power SystemsGraph Attention Networks

    School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA · Department of Electrical Engineering, Columbia University, New York, NY, USA · School of Business, University of California, Riverside, Riverside, CA, USA

  28. Competition-Aware CPC Forecasting with Near-Market Coverage

    Mar 13, 2026Sebastian Frey, Edoardo Beccari, Maximilian Kranz +4Competitive AnalysisOnline Advertising

    *Nova School of Business and Economics, Portugal · †University of Hamburg, Germany

  29. TRACE: Temporal Rule-Anchored Chain-of-Evidence on Knowledge Graphs for Interpretable Stock Movement Prediction

    Mar 12, 2026Qianggang Ding, Haochen Shi, Luis Castejón Lozano +7Stock Price ForecastingFinance

    DIRO & Institut Courtois, Université de Montréal, Montreal, QC, Canada · Mila – Québec AI Institute, Montreal, QC, Canada · Aily Labs, Madrid, Spain +2

  30. Overcoming the Modality Gap in Context-Aided Forecasting

    Mar 12, 2026Vincent Zhihao Zheng, Étienne Marcotte, Arjun Ashok +4Synthetic Data AugmentationMultimodal Pretraining

    ServiceNow AI Research, Montréal, Canada · Department of Civil Engineering, McGill University, Montréal, Canada · DIRO, Université de Montréal, Montréal, Canada +1