Time Series Forecasting

Ask about this topic

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

876 papers143 papers in the last four weeks, up 32% on the four weeks before. 0.8% of all new papers.

  1. Impermanent: A Live Benchmark for Temporal Generalization in Time Series Forecasting

    Mar 9, 2026Azul Garza, Renée Rosillo, Rodrigo Mendoza-Smith +5Forecasting BenchmarksTime Series Forecasting

    TimeCopilot · Independent Researcher · ELLIS Institute Tübingen +3

  2. Are We Winning the Wrong Game? Revisiting Evaluation Practices for Long-Term Time Series Forecasting

    Mar 9, 2026Thanapol Phungtua-eng, Yoshitaka YamamotoTime Series ForecastingLong-Term Time Series Forecasting

    Shizuoka University, Shizuoka, Japan

  3. Hybrid Quantum Neural Network for Multivariate Clinical Time Series Forecasting

    Mar 9, 2026Irene Iele, Floriano Caprio, Paolo Soda +1Multivariate Time Series ForecastingTime Series Forecasting

    Unit of Artificial Intelligence and Computer Systems, Università Campus Bio-Medico di Roma, Italy · Department of Diagnostics and Intervention, Radiation Physics, Biomedical Engineering, Umeå University, Sweden · Department of Naval, Electrical, Electronics and Telecommunications Engineering, University of Genoa, Italy

  4. BrainCast: A Spatio-Temporal Forecasting Model for Whole-Brain fMRI Time Series Prediction

    Mar 9, 2026Yunlong Gao, Jinbo Yang, Li Xiao +5Time Series ForecastingSpatiotemporal Forecasting

    Institute of Advanced Technology, University of Science and Technology of China, Hefei 230052, China. · MoE Key Laboratory of Brain-Inspired Intelligence Perception and Cognition, University of Science and Technology of China, Hefei 230052, China. · School of Mathematics and Computer Sciences, Nanchang University, Nanchang 330031, China. +3

  5. GCGNet: Graph-Consistent Generative Network for Time Series Forecasting with Exogenous Variables

    Mar 9, 2026Zhengyu Li, Xiangfei Qiu, Yuhan Zhu +4Exogenous Time Series ForecastingRobust Time Series Forecasting

    East China Normal University

  6. Uncertainty-Gated Generative Modeling

    Mar 8, 2026Xingrui Gu, Haixi ZhangTime Series ForecastingGenerative Modeling

    Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA, USA · School of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA

  7. TS-MLLM: A Multi-Modal Large Language Model-based Framework for Industrial Time-Series Big Data Analysis

    Mar 8, 2026Haiteng Wang, Yikang Li, Yunfei Zhu +3Multimodal Large Language ModelsTime Series Forecasting

    School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China · School of Software, Beihang University, Beijing 100191, China · Hangzhou International Innovation Institute, Beihang University, Hangzhou 311115, China +3

  8. Turning Time Series into Algebraic Equations: Symbolic Machine Learning for Interpretable Modeling of Chaotic Time Series

    Mar 7, 2026Madhurima Panja, Grace Younes, Tanujit ChakrabortyTime Series ForecastingChaotic Time-Series Prediction

    SAFIR, Sorbonne University Abu Dhabi, UAE · Sorbonne Center for Artificial Intelligence, Sorbonne University, Paris, France

  9. Hierarchical Industrial Demand Forecasting with Temporal and Uncertainty Explanations

    Mar 6, 2026Harshavardhan Kamarthi, Shangqing Xu, Xinjie Tong +4Explainable Time Series ForecastingTime Series Forecasting

    Georgia Institute of Technology Atlanta, USA · Aspen Technology Houston, USA · The Dow Chemical Company Houston, USA +1

  10. Stock Market Prediction Using Node Transformer Architecture Integrated with BERT Sentiment Analysis

    Mar 6, 2026Mohammad Al Ridhawi, Mahtab Haj Ali, Hussein Al OsmanStock Price ForecastingFinancial Forecasting

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

  11. Aura: Universal Multi-dimensional Exogenous Integration for Aviation Time Series

    Mar 5, 2026Jiafeng Lin, Mengren Zheng, Simeng Ye +5Exogenous Time Series ForecastingTime Series Forecasting

    School of Software, BNRist, Tsinghua University, Beijing, China · Hongshen College, Chongqing University, Chongqing, China · School of Software, Tsinghua University, Beijing, China +1

  12. Retrieval-Augmented Generation with Covariate Time Series

    Mar 5, 2026Kenny Ye Liang, Zhongyi Pei, Huan Zhang +3Time Series Forecasting with CovariatesRetrieval-Augmented Time Series Forecasting

    Tsinghua University · China Southern Airlines

  13. SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms

    Mar 5, 2026Longkun Xu, Xiaochun Zhang, Qiantu Tuo +1Time Series ForecastingCode Generation

    Ecoflow Inc.

  14. Timer-S1: A Billion-Scale Time Series Foundation Model with Serial Scaling

    Mar 5, 2026Yong Liu, Xingjian Su, Shiyu Wang +7Time Series ForecastingTime-Series Foundation Models

    Tsinghua University · ByteDance

  15. SELDON: Supernova Explosions Learned by Deep ODE Networks

    Mar 4, 2026Jiezhong Wu, Jack O'Brien, Jennifer Li +6AstrophysicsIrregular Time-Series Modeling

    NSF-Simons AI Institute for the Sky (SkAI), Chicago, IL, USA · Department of Industrial Engineering and Management Sciences, Northwestern University · Department of Astronomy, University of Illinois Urbana-Champaign +4

  16. PatchDecomp: Interpretable Patch-Based Time Series Forecasting

    Mar 4, 2026Hiroki Tomioka, Genta YoshimuraTime Series ForecastingExplainable Time Series Forecasting

    Mitsubishi Electric Corporation, Japan

  17. Harmonic Dataset Distillation for Time Series Forecasting

    Mar 4, 2026Seungha Hong, Sanghwan Jang, Wonbin Kweon +3Frequency-Domain Time Series ModelingDataset Distillation

    Pohang University of Science and Technology (POSTECH), Republic of Korea · University of Illinois Urban-Champaign (UIUC), United States

  18. XLinear: Frequency-Enhanced MLP with CrossFilter for Robust Long-Range Forecasting

    Mar 4, 2026Xiang AoFrequency-Domain Time Series ModelingRobust Time Series Forecasting

    School of Software Engineering, Beijing Jiaotong University, Beijing, China

  19. Towards Accurate and Interpretable Time-series Forecasting: A Polynomial Learning Approach

    Mar 3, 2026Bo Liu, Shao-Bo Lin, Changmiao Wang +1Time Series ForecastingExplainable Time Series Forecasting

    Center for Intelligent Decision-Making and Machine Learning, School of Management, Xi’an Jiaotong University, Xi’an, China · The 39th Research Institute of China Electronics Technology Group Corporation, Xi’an, China · Shenzhen Research Institute of Big Data, ShenZhen, China

  20. FinTexTS: Financial Text-Paired Time-Series Dataset via Semantic-Based and Multi-Level Pairing

    Mar 3, 2026Jaehoon Lee, Suhwan Park, Taeyoon Lim +9Financial Time SeriesTime Series Forecasting

    LG AI Research · Ulsan National Institute of Science and Technology

  21. Same Error, Different Function: The Optimizer as an Implicit Prior in Financial Time Series

    Mar 3, 2026Federico Vittorio Cortesi, Giuseppe Iannone, Giulia Crippa +2Neural Network OptimizationFinancial Time Series

    Massachusetts Institute of Technology, Cambridge, MA, USA · Princeton University, Princeton, NJ, USA.

  22. How do standard time series forecasting benchmarks translate to finance? A broad study of risk adjusted performance

    Mar 2, 2026Adir Saly-Kaufmann, Kieran Wood, Jan-Peter Calliess +1Financial Time SeriesTime Series Forecasting

    Machine Learning Research Group, Department of Engineering Science, University of Oxford · Oxford-Man Institute of Quantitative Finance, University of Oxford

  23. Fed-GAME: Personalized Federated Learning with Graph Attention Mixture-of-Experts For Time-Series Forecasting

    Mar 2, 2026Yi Li, Han Liu, Mingfeng Fan +3Federated LearningFederated Graph Learning

    School of Automation, Central South University · Department of Electrical and Computer Engineering, National University of Singapore · Department of Mechanical Engineering, National University of Singapore +2

  24. A Deep Learning Framework for Heat Demand Forecasting using Time-Frequency Representations of Decomposed Features

    Mar 1, 2026Adithya Ramachandran, Satyaki Chatterjee, Thorkil Flensmark B. Neergaard +3Time Series ForecastingMultivariate Time Series Forecasting

  25. Learning with the Nash-Sutcliffe loss

    Mar 1, 2026Hristos Tyralis, Georgia PapacharalampousMultivariate Time Series ForecastingTime Series Forecasting

    1Support Command, Hellenic Air Force, Elefsina Air Base, 19 200, Elefsina, Greece · Department of Land, Environment, Agriculture and Forestry, University of Padova, Viale dell'Università 16, 35020, Legnaro, Italy

  26. Retrodictive Forecasting: A Proof-of-Concept for Exploiting Temporal Asymmetry in Time Series Prediction

    Feb 28, 2026Cedric DamourTime Series Forecasting

    ENERGY-Lab, Université de La Réunion, Saint-Denis, La Réunion, France

  27. Adapt Data to Model: Adaptive Transformation Optimization for Domain-shared Time Series Foundation Models

    Feb 28, 2026Yunzhong Qiu, Zhiyao Cen, Zhongyi Pei +2Time Series ForecastingTime-Series Foundation Models

    School of Software, BNRist, Tsinghua University, China

  28. HURRI-GAN: A Novel Approach for Hurricane Bias-Correction Beyond Gauge Stations using Generative Adversarial Networks

    Feb 27, 2026Noujoud Nadera, Hadi Majed, Stefanos Giaremis +4Spatiotemporal ForecastingFlood Forecasting

    Center of Computation and Technology, Louisiana State University, Baton Rouge, 70803 LA, US · Saint-Joseph University of Beirut, Beirut, 1104, Lebanon · Department of Physics, Aristotle University of Thessaloniki, Thessaloniki , 54124, Greece +3

  29. A Controlled Comparison of Deep Learning Architectures for Multi-Horizon Financial Forecasting: Evidence from 918 Experiments

    Feb 27, 2026Nabeel Ahmad SaiddTime Series ForecastingForecasting Benchmarks

    Dr. A.P.J. Abdul Kalam Technical University (AKTU)

  30. SDMixer: Sparse Dual-Mixer for Time Series Forecasting

    Feb 27, 2026Xiang AoMultivariate Time Series ForecastingTime Series Forecasting

    School of Software Engineering, Beijing Jiaotong University, Beijing, China