Probabilistic Time Series Forecasting

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Overview

Probabilistic time series forecasting studies not only what may happen next, but how uncertain that prediction is, often by producing quantiles, intervals, or complete future scenarios. Approaches range from Bayesian and statistical models, quantile regression, and conformal calibration to ensembles, diffusion and flow-based generators, and pretrained time-series foundation models. These methods are evaluated for accuracy, calibration, sharpness, and computational cost across settings such as energy, finance, health, and traffic, with increasing attention to multivariate dependence, irregular observations, and distribution shifts. A central tension is that better point accuracy does not guarantee reliable uncertainty: performance can vary across horizons and regimes, and foundation models do not consistently outperform simpler task-specific methods.

Latest papers

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162 papers23 papers in the last four weeks, down 15% on the four weeks before. 0.1% of all new papers.

  1. Timestral

    Oct 27, 2026Adrien Petralia, Alexandre Gavaudan, Artjom Joosen +353Time Series ForecastingTime-Series Foundation Models

  2. Probabilistic Machine Learning for Short-Term Atmospheric Seeing Forecasting

    Oct 21, 2026Mary-Joe Medlej, Rahul Srinivasan, Simon Prunet +2Probabilistic Time Series Forecasting

    Universit´e Cˆote d’Azur, Observatoire de la Cˆote d’Azur, J.L. Lagrange, Parc Valrose 06108 Nice Cedex 2, France · SISSA, Via Bonomea 265, 34136 Trieste, Italy · IFPU - Institute for Fundamental Physics of the Universe, Via Beirut 2, 34014 Trieste, Italy

  3. Dynamic Dual-Feedback Conformal Inference for Time Series Forecasting

    Oct 19, 2026Songlin Du, Ling Luo, Uwe AickelinConformal PredictionAdaptive Conformal Inference

    Faculty of Engineering and Information Technology, School of Computing and Information Systems, University of Melbourne

  4. Probabilistic Limit Order Book Forecasting with Conditional Diffusion Models

    Oct 18, 2026Junyu Chen, Franklin Liu, Moshu Xu +1Limit Order Book ForecastingLimit Order Book Modeling

    Department of Statistics and Data Science, Tsinghua University, Beijing, China

  5. Data-driven forecasting of tropical cloud forest phenology: A dynamical systems and machine learning hybrid approach

    Oct 18, 2026Pedro Garcia, Saul FloresTime Series ForecastingTime Series Forecasting with Covariates

    Departamento de Física, Facultad de Ingeniería, Universidad Católica Andrés Bello, Caracas, Venezuela · Laboratorio de Ecología de Suelos, Centro de Ecología, Instituto Venezolano de Investigaciones Científicas, Caracas, Venezuela

  6. Morpheus-2.0: Multiscale Probabilistic Forecasting with Dual-Axis Attention

    Oct 16, 2026Aakriti, Manoj Cherukumalli, Prathamesh Patil +5Time Series ForecastingProbabilistic Time Series Forecasting

  7. PathFM: Fast Generative Forecasting of Multivariate Trajectories

    Oct 15, 2026Jiachen Yao, Xiyuan Zhang, Annan Yu +5Time Series ForecastingMultivariate Time Series Forecasting

    California Institute of Technology · Amazon

  8. Quantile-Guided Diffusion for Probabilistic Time-Series Forecasting

    Oct 14, 2026Shadi Omari, Bashar Khoury, Assaf SchusterProbabilistic Time Series ForecastingDiffusion Guidance

    Department of Computer Science, Technion – Israel Institute of Technology

  9. State-Matched Sequence Conformal Prediction

    Oct 14, 2026Ruihang Han, Li-Hsiang LinConformal PredictionProbabilistic Time Series Forecasting

    Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30303

  10. Deterministic Prediction as Global Velocity: Flow Matching for Probabilistic Time-Series Forecast

    Oct 13, 2026Jiajing Hu, Xu Han, Li-Ping LiuTime Series ForecastingProbabilistic Time Series Forecasting

    Department of Computer Science, Tufts University

  11. Nearest Neighbor Functional Curve Completion for Intraday Probabilistic Revisions of Renewable Generation Forecasts

    Oct 12, 2026Guillermo Terrén-Serrano, Michael LudkovskiProbabilistic Time Series ForecastingTime Series Forecasting

    Environmental Markets Lab (emLab), University of California Santa Barbara, Santa Barbara, CA, USA. · Environmental Studies Program, University of California Santa Barbara, Santa Barbara, CA, USA. · Statistics and Applied Probability, University of California Santa Barbara, Santa Barbara, CA, USA.

  12. OceanFlow: Coherent Flow Matching for Probabilistic Ocean Modeling

    Oct 11, 2026Yuan Gao, Fan Xu, Hao Wu +1Probabilistic ForecastingFlow Matching

    Tsinghua University · University of Science and Technology of China

  13. Probabilistic Forecasting of Electric Vehicle Charging in a Time-varying Hierarchical Infrastructure

    Oct 9, 2026Guillaume Principato, Yvenn Amara-Ouali, Yannig Goude +2Electric Vehicle ChargingProbabilistic Time Series Forecasting

    Laboratoire de Mathematiques d’Orsay, Université Paris-Saclay, CNRS, INRIA · Electricité de France R&D · Université Paris-Cité

  14. Seq-Flow: Efficient Probabilistic Forecasting with Self-Rollout Error Control

    Oct 7, 2026Yinan Huang, Shitij Govil, Bo Dai +1Probabilistic ForecastingProbabilistic Time Series Forecasting

    Georgia Institute of Technology

  15. From Shared Demand Patterns to Local Uncertainty: Probabilistic Load Forecasting by Mixing Compact Adaptations

    Oct 6, 2026Haoran Li, Zhe Cheng, Yang WengElectricity Load ForecastingProbabilistic Time Series Forecasting

  16. Machine Learning for German Redispatch Forecasting under Data Delays and Temporal Distribution Shift

    Oct 6, 2026Faraz Shamim, Faris ShamimDistribution Shift RobustnessTime Series Forecasting

    KIST Medical College and Teaching Hospital, Nepal · OTH Regensburg

  17. MercerFlow: Flow Matching in a Kernel-Induced Latent Space for Probabilistic Forecasting

    Oct 5, 2026Ilya Kuleshov, Egor Serov, Alexey ZaytsevMultivariate Time Series ForecastingConditional Flow Matching

    Applied AI Institute Moscow, Russia

  18. Skillful Data-Driven Subseasonal Soil Moisture Forecasting: Prospects and Limits for Flash Drought Prediction

    Oct 5, 2026Noelia Otero, Atahan Özer, Miguel-Ángel Fernández-Torres +1Spatiotemporal ForecastingProbabilistic Time Series Forecasting

    Applied Machine Learning Group, Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, Berlin, Germany · Department of Signal Theory and Communications, Universidad Carlos III de Madrid (UC3M), Madrid, Spain

  19. Pythia: Toward Foundation World Models for Multimodal Time Series

    Oct 4, 2026Xilin Dai, Hongzhou Chen, Yifan Hu +3Multivariate Time Series ForecastingWorld Model Learning

    Ant International

  20. TIMBRE: Teaching Time Series Forecasters to Read, Remember, and Reconcile

    Oct 3, 2026Xinyu Guan, Zhirong Zhang, Hongyuan Liu +4Time Series ForecastingRetrieval-Augmented Time Series Forecasting

    Alibaba Group · Chang’an University · University of Electronic Science and Technology of China +4

  21. TMAML: Temporal Model-Agnostic Meta-Learning for Cold-Start Time Series Forecasting

    Oct 3, 2026Wannes Janssens, Matthias Bogaert, Dirk Van den PoelTime Series ForecastingMeta-Learning

    Ghent University, Research Group Data Analytics, Ghent, Belgium

  22. GARDiff: Graph-Aligned Residual Diffusion for Probabilistic Multivariate Time-Series Forecasting

    Sep 29, 2026Rui Han, Min Yang, Xu Zhang +3Multivariate Time Series ForecastingGraph Structure Learning

    Shandong University, Jinan, China · Macquarie University, Sydney, Australia · China University of Petroleum (East China), Qingdao, China +1

  23. Variational Augmented Invertible Koopman Autoencoder for probabilistic time series forecasting

    Sep 29, 2026Anthony Frion, Lucas Drumetz, Guillaume Tochon +3Probabilistic Time Series ForecastingLong-Term Time Series Forecasting

    Institute of coastal modelling Helmholtz-Zentrum Hereon · IMT Atlantique Lab-STICC, UMR CNRS 6285, Brest, France · LRE EPITA, Le Kremlin-Bicêtre, France +1

  24. KiT: A Foundation Model for Financial Time-Series Forecasting using DiffusionTransformers

    Sep 28, 2026Boyu Zhang, Haorui LiDiffusion TransformerFinancial Forecasting

    University of California, Los Angeles · Southeast University

  25. ViBR-WM: Visual Bayesian Regression for World Modeling

    Sep 27, 2026Jifan Li, Ning NingWorld Model LearningTime Series Forecasting

    Department of Statistics, Texas A&M University College Station, TX 77843

  26. TimeES: Probabilistic and Deterministic Time Series Forecasting via Evolutionary Spectra

    Sep 26, 2026Weiwei Ye, Renhe Jiang, Hangchen Liu +2Non-Stationary Time Series ForecastingProbabilistic Time Series Forecasting

    The University of Tokyo

  27. STRIDE: State-Transition Representation via Increment Dynamics and Evolution

    Sep 26, 2026Yuchen Xiong, Siming Huang, Jianfeng SunTime Series ForecastingProbabilistic Time Series Forecasting

  28. DiffPTS: Rethinking Diffusion ELBO for Probabilistic Time Series Forecasting

    Sep 26, 2026Weiwei Ye, Dongyuan Li, Hangchen Liu +3Time Series ForecastingProbabilistic Time Series Forecasting

    The University of Tokyo · Harbin Institute of Technology, Shenzhen

  29. Fracast-0: Fractal Weight Sharing for a Time Series Foundation Model with Only 85K Parameters

    Sep 26, 2026Tianxiang Zhan, Huanyao Zhang, Yuanpeng HeTime-Series Foundation ModelsProbabilistic Time Series Forecasting

    University of Electronic Science and Technology of China · Peking University

  30. Aurora-X: Built for Extreme Time Series Forecasting

    Sep 25, 2026Xingjian Wu, Chenjuan Guo, Xiangfei Qiu +6Time Series ForecastingTime-Series Foundation Models

    East China Normal University