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

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

  1. NECA: Neighbor Event Curve Augmentation for Multi-Horizon ICU Deterioration Prediction

    Oct 29, 2026Chenyang Wang, Jiawei Theresa Tang, Xinran Liu +2Clinical Outcome PredictionClinical Risk Prediction

    Department of Statistics and Data Science, National University of Singapore, Singapore · School of Computing, National University of Singapore, Singapore · Institute for Infocomm Research (I2R), A*STAR, Singapore

  2. Multistep and Multivariate Time Series Explainability with GradientSHAP: A Wind Power Case Study

    Oct 29, 2026Robbie Southam, Zhong Fan, Ke LiExplainable Time Series ForecastingWind Power Forecasting

  3. FARE: Factor-Aware Retrieval with Error-Guided Fusion for Retail Forecasting

    Oct 29, 2026Chenghao Gu, Zhuokang Shen, Shenghao Wu +3Time Series ForecastingRetrieval-Augmented Time Series Forecasting

    East China Normal University, Shanghai, China · China Merchants Bank Credit Card Center, Shanghai, China

  4. A Deep Learning Framework for Quantile Demand Forecasting in E-commerce with Doubly Censored Data

    Oct 29, 2026Ziwen Ye, Jiawen Wei, Teng Song +2Uncertainty QuantificationQuantile Regression

    Meituan, Beijing, China

  5. Learning Kolmogorov Backward Operators for Spectral Analysis and Forecasting: A Data-Driven Variational Galerkin Framework

    Oct 29, 2026Yuanchao Xu, Claire Valva, Ben Gao +1Operator LearningTime Series Forecasting

    Department of Mathematics, Graduate School of Science, Kyoto University, Kyoto 606-8502, Japan · Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA 91125, USA · Laboratoire Hubert Curien, UMR 5516, CNRS, IOGS, INRIA, Université Jean Monnet, 18 Rue du Professeur Benoît Lauras, 42000 Saint-Étienne, France

  6. IMRouter: Imbalance-aware Temporal Pattern Routing for LLM-based Time Series Forecasting

    Oct 29, 2026Xin Yang, Cai Xu, Haishun Chen +4Time Series ForecastingLLM-Based Time Series Forecasting

    Xidian University, Xi’an, Shaanxi, China · Chang’an University, Xi’an, Shaanxi, China

  7. The Utility of Physics-Informed Machine Learning in Solar Power Production Forecasting

    Oct 28, 2026Peter Pavlík, Franz M. Rohrhofer, Bernhard C. GeigerSolar Power ForecastingPhysics-Informed ML

    Kempelen Institute of Intelligent Technologies, Sky Park Offices, Bottova 7939/2A, Bratislava, 811 09, Slovakia · Faculty of Information Technology, Brno University of Technology, Božetěchova 2, Brno, 612 00, Czech Republic · Know Center Research GmbH, Sandgasse 34, Graz, 8010, Austria +2

  8. REVBRAIN: Real-time Probabilistic EEG Forecasting Using Residual Vector Quantization

    Oct 28, 2026Hanna Pankka, Jaakko Lehtinen, Timo RoineTime Series ForecastingProbabilistic Time Series Forecasting

    Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Finland · Department of Computer Science, Aalto University School of Science, Finland · NVIDIA, Finland +1

  9. FACTS-MAS: A Multi-Agent Architecture for Adaptive Forecasting from Heterogeneous Evidence

    Oct 28, 2026Madumita Karthikeyan, Umang Rajnikant Bid, Rong PanTime Series ForecastingAgentic Time Series Forecasting

  10. From Next Day Wildfire to Next Days Wildfire: A New Multi-Continent Dataset of Active-Fire Spread for Sequence-to-Sequence Forecasting

    Oct 28, 2026Jose Guillen, Renzo Zanca, Valentin BarriereWildfire ForecastingTime Series Forecasting

    CENIA, Macul, Chile · Universidad de Chile, DCC, Santiago, Chile

  11. Timestral

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

  12. RankFormer: Rethinking Time Series Transformers through Representation Capacity Analysis and Progressive Decoding

    Oct 27, 2026Peiwang Tang, Cheng HE, Xijie Liang +1Multivariate Time Series ForecastingTime Series Forecasting

    University of Science and Technology of China, Hefei, Anhui, China · State Key Laboratory of Cognitive Intelligence, Hefei, Anhui, China · Shanghai Black Wing Asset Management, Shanghai, China

  13. TimeWorld: Towards Action-Conditioned Multimodal World Models for Time Series Forecasting

    Oct 26, 2026Hang Ni, Weijia Zhang, Hao LiuTime Series ForecastingAction-Conditioned World Models

    The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China

  14. Dynamic Multi-Step Decoding for Time-Series Foundation Models

    Oct 25, 2026Birmjune Kim, Hyungju Lee, Hyun Oh SongTime Series ForecastingTime-Series Foundation Models

    Department of Computer Science and Engineering, Seoul National University · Interdisciplinary Program in Artificial Intelligence, Seoul National University

  15. MetaARIMA: Configuration-Level Transfer Learning for ARIMA Models

    Oct 25, 2026Vitor Cerqueira, Ricardo Inácio, Carlos SoaresTime Series ModelingTime Series Forecasting

    University of Coimbra; CISUC/LASI – Centre for Informatics and Systems of the University of Coimbra; Coimbra, Portugal · Faculty of Engineering, University of Porto; Porto, Portugal · Faculty of Engineering, University of Porto; Laboratory for Artificial Intelligence and Computer Science (LIACC), Portugal; Fraunhofer Portugal AICOS, Portugal; Porto, Portugal

  16. Benchmarking System One Models for Time-Series Decision Making: A Case Study of Jev

    Oct 24, 2026Jianye Wang, Kexin Zhang, Jiayin Xiong +1Time Series ClassificationTime Series Forecasting

    The Hong Kong University of Science and Technology (Guangzhou)

  17. DBCM: Dual-Branch Calibration Module for Test-Time Adaptation in Time Series Forecasting

    Oct 23, 2026Jaebyeong Jeon, Kunwoo Kang, Sang Yup Lee +1Time Series ForecastingContinual Test-Time Adaptation

    Department of Statistics and Data Science, Yonsei University · Digital Analytics, College of Computing, Yonsei University · Department of Communication, Yonsei University

  18. A Model-Agnostic Correction Framework for Short-Term Building Load Forecasting

    Oct 22, 2026Shiqiao Zhou, Huanbo Lyu, Holger Schöner +5Electricity Load ForecastingTime Series Forecasting

    School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT, West Midlands, United Kingdom · Siemens AG, Munich, 80333, Bavaria, Germany · School of Mathematics, University of Birmingham, Edgbaston, Birmingham, B15 2TT, West Midlands, United Kingdom +1

  19. Forecasting Associations, Not Interventions: A Preregistered Causal Audit of Covariate-Aware Time Series Foundation Models

    Oct 22, 2026Zong-Han BaiTime-Series Foundation ModelsCausal Effect Estimation

    National Tsing Hua University, Hsinchu, Taiwan.

  20. Reducing Multi-Horizon Photovoltaic Forecast Error through Tree-Anchored Expert Combination

    Oct 22, 2026Sun Ze, Zhou Liguo, Xu Yuqing +3Solar Power ForecastingTime Series Forecasting

    School of Computer Science and Technology, Huaibei Normal University, China · Chair of Robotics, Artificial Intelligence and Real-time Systems, Technical University of Munich, Germany

  21. Is spectral predictability enough? Testing Ω-matching for synthetic pretraining under distribution shift

    Oct 22, 2026Edric Castel C. Hao, Juan Raphael S. Seña, Neon S. De JesusSynthetic Data PretrainingTime Series Forecasting

    Analog Devices, Inc.

  22. Rethinking Agentic Model Orchestration for Time Series Forecasting

    Oct 21, 2026Tong Guan, Tianxiang Zhan, Shirui Pan +1Agentic Time Series ForecastingTime Series Forecasting

    Griffith University · Zhejiang University

  23. Data-driven and physics-guided hindcasting of measured wave spectra

    Oct 21, 2026Sander RikkaTime Series ForecastingPhysics-Informed ML

    Department of Marine Systems, Tallinn University of Technology

  24. Asymmetric Bidirectional Predictive Dynamics in Google Search and COVID-19 Time Series: A Multi-Horizon Forecast-Error Analysis

    Oct 20, 2026Andrei Velichko, Imen MahmoudTime Series ForecastingEpidemic Forecasting

    Institute of Physics and Technology, Petrozavodsk State University, 33 Lenina Prospekt, Petrozavodsk 185910, Republic of Karelia, Russia · University of Mannouba, Tunisia · Laboratory of Research in Innovative and Management, Risk, Accounting and Finance

  25. GraphCast-Mamba: Learning Non-Markovian Corrections for Weather Forecasting

    Oct 20, 2026Ilya Vilkoviskiy, Liang-Hong Mo, Suozhi Huang +1Weather ForecastingTime Series Forecasting

    Department of Physics, Princeton University, Princeton, NJ 08544, USA · Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ 08544, USA · École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland +2

  26. Model- and Layer-Level Closed-Loop Forecasting with SSM-Based Spiking Neural Networks

    Oct 20, 2026Erik Stolt, Sanja Karilanova, Ayca OzcelikkaleTime Series ForecastingSpiking Neural Networks

    Department of Electrical Engineering, Uppsala University, Uppsala, Sweden

  27. Meta-iLaD: Identifiable Latent Dynamics via Meta-Learning of Dynamics Environments

    Oct 19, 2026Yubo Ye, Sweekar Piya, Xiajun Jiang +1Latent Dynamics ModelingTime Series Forecasting

    Department of Computing and Information Sciences, Rochester Institute of Technology, Rochester, New York, USA · Department of Computer Science, Rowan University, Glassboro, New Jersey, USA

  28. A Hybrid TFT-NBEATS Framework for Robust Multi-Horizon Photovoltaic Power Forecasting

    Oct 19, 2026Shafi Bin Sultan, Sabik Bin Sultan, Mohammad Tajrian Arafat Alvi +2Solar Power ForecastingTime Series Forecasting

    St. Joseph Higher Secondary School, Dhaka, Bangladesh · Bangladesh Air Force Shaheen College, Kurmitolla, Dhaka, Bangladesh · Computer Science & Engineering, Jahangirnagar University, Savar, Bangladesh +2

  29. WhatIf-Bench: Benchmarking Intervention-Aware Time Series Forecasting

    Oct 19, 2026Arjun Ashok, Mihir Parmar, Palash Goyal +6Time Series ForecastingTime Series Forecasting with Covariates

    Google · Mila - Quebec AI Institute · Université de Montréal +1

  30. CTLite: Lightweight Irregular Multivariate Time Series Forecasting with Reusable Continuous-Time Summaries

    Oct 19, 2026Shusen Ma, Xudong Zuo, Yangchun Xie +1Multivariate Time Series ForecastingTime Series Modeling

    Institute of Advanced Technology, University of Science and Technology of China, Hefei, China · Department of Automation, University of Science and Technology of China, Hefei, China