Time Series Forecasting

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139 papers in the last four weeks, up 101% on the four weeks before. 0.9% of all new papers.

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Hedging Memory Horizons for Non-Stationary Prediction via Online Aggregation
May 7, 2026Yutong Wang, Yannig Goude, Qiwei YaoEnsemble Learning Time Series Forecasting
Department of Statistics, LSE · Électricité de France R&D
Perceive, Route and Modulate: Dynamic Pattern Recalibration for Time Series Forecasting
May 7, 2026Siru Zhong, Zhao Meng, Haohuan Fu +3Dynamic Neural Networks Time Series Forecasting
The Hong Kong University of Science and Technology (Guangzhou) · Tsinghua University · Squirrel Ai Learning
SWIFT: Spatio-temporal Wavelet Integrated Forecasting Framework for Workload Traces
May 7, 2026Zeyuan Ding, Lingfeng Zheng, Dian Ding +1Multivariate Time Series Forecasting Time Series Forecasting
1Shanghai Jiao Tong University, Shanghai, China · 2Shaanxi Normal University, Xi’an, China
Gated QKAN-FWP: Scalable Quantum-inspired Sequence Learning
May 7, 2026Kuo-Chung Peng, Samuel Yen-Chi Chen, Jiun-Cheng Jiang +16Time Series Forecasting Quantum-Inspired ML
Department of Physics and Center for Theoretical Physics, National Taiwan University, Taipei, Taiwan · National Center for High-Performance Computing, National Institutes of Applied Research, Hsinchu, Taiwan · Wells Fargo, New York, NY, USA +11
Does Synthetic Data Help? Empirical Evidence from Deep Learning Time Series Forecasters
May 7, 2026Hugo Cazaux, Eyjólfur Ingi Ásgeirsson, Hlynur StefánssonSynthetic Data Augmentation Synthetic Data Generation
Department of Engineering Reykjavík University Iceland, Menntavegur 1, 102
AirQualityBench: A Realistic Evaluation Benchmark for Global Air Quality Forecasting
May 7, 2026Xing Xu, Xu Wang, Yudong Zhang +3Benchmark Design Time Series Forecasting
University of Science and Technology of China (USTC), Hefei, Anhui, China · 2Suzhou Institute for Advanced Research, USTC, Suzhou, Jiangsu, China · 3The Hong Kong Polytechnic University, Hong Kong, China
Multi-Dimensional Behavioral Evaluation of Agentic Stock Prediction Systems Using Large Language Model Judges with Closed-Loop Reinforcement Learning Feedback
May 7, 2026Mohammad Al Ridhawi, Mahtab Haj Ali, Hussein Al OsmanTime Series Forecasting AI Agent Evaluation
School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Canada
Temporal Functional Circuits: From Spline Plots to Faithful Explanations in KAN Forecasting
May 7, 2026Naveen MysoreExplainable Time Series Forecasting Explainable Artificial Intelligence
University of California, Santa Barbara
Superposition Is Not Necessary: A Mechanistic Interpretability Analysis of Transformer Representations for Time Series Forecasting
May 6, 2026Alper YıldırımTransformer Interpretability Time Series Forecasting
Forecasting Green Skill Demand in the Automotive Industry: Evidence from Online Job Postings
May 6, 2026Sabur Butt, Joshua N. Arrazola E., Hector G. Ceballos +1Time Series Forecasting
Institute for the Future of Education, Tecnológico de Monterrey, Monterrey, 64849, Mexico · Universidad Politécnica de Victoria, Victoria, Mexico
Forecasting Oncology Demand Trends with Boosting-Based Bayesian Conjugate Models
May 6, 2026Ademir Batista dos Santos Neto, Tiago Alessandro Espinola Ferreira, Paulo Renato Alves FirminoBayesian Inference Time Series Forecasting
Retrieval Mechanisms Surpass Long-Context Scaling in Time Series Forecasting
May 6, 2026Rishi Ahuja, Kumar Prateek, Simranjit Singh +1Time Series Forecasting Long-Context Modeling
Department of Information Technology, Dr. B.R. Ambedkar National Institute of Technology Jalandhar, Punjab, 144008, India.
Event-Based Early Warning of Vineyard Disease Risk from Environmental Time Series
May 6, 2026Ivica Dimitrovski, Ivan Kitanovski, Danco Davcev +2Event Time Prediction Time Series Forecasting
Faculty of Computer Science and Engineering University Ss Cyril and Methodius Skopje 1000, North Macedonia
Training-Free Probabilistic Time-Series Forecasting with Conformal Seasonal Pools
May 5, 2026Valery ManokhinTime Series Forecasting Conformal Prediction
Independent researcher.
Global and Local Topology-Aware Attention with Persistent Homology and Euler Biases for Time-Series Forecasting
May 4, 2026Usef Faghihi, Amir SakiTime Series Forecasting Persistent Homology
Department of Mathematics and computer science · University of Quebec Trois Rivieres
Foundation Models to Unlock Real-World Evidence from Nationwide Medical Claims
May 4, 2026Fan Ma, Yuntian Liu, Xiang Lan +22Healthcare Time Series Forecasting
Department of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA · Department of Medical, Surgical and Health Sciences, Università degli Studi di Trieste, Trieste, Italy · Applied Mathematics and Computational Science Graduate Group, University of Pennsylvania, Philadelphia, PA, USA +6
Toward a foundational thermal model for residential buildings
May 2, 2026Ting-Yu Dai, Kingsley Nweye, Dev Niyogi +1Time Series Forecasting Physics-Informed ML
The University of Texas at Austin · Eindhoven University of Technology
Forecasting Source Stability in Scientific Experiments using Temporal Learning Models: A Case Study from Tritium Monitoring
May 2, 2026Nicholas Tan Jerome, Nadia Aouadi, Christoph Koehler +2Event Time Prediction Long-Term Time Series Forecasting
Institute for Data Processing and Electronics, Karlsruhe Institute of Technology, Germany · Schmalkalden University of Applied Sciences, Schmalkalden, Germany · Technical University Munich, Garching, Germany +1
CombinationTS: A Modular Framework for Understanding Time-Series Forecasting Models
May 2, 2026Xiaorui Wang, Fanda Fan, Chenxi Wang +9Time Series Forecasting Forecasting Benchmarks
Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China · University of Chinese Academy of Sciences, Beijing, China · Beijing Normal University - Hong Kong Baptist University United International College, Zhuhai, China +1
From Prediction to Practice: A Task-Aware Evaluation Framework for Blood Glucose Forecasting
May 1, 2026Alireza Namazi, Heman ShakeriHealthcare Clinical Decision Support
Department of Computer Science University of Virginia Charlottesville, VA, USA · School of Data Science University of Virginia Charlottesville, VA, USA
PAMod: Modeling Cyclical Shifts via Phase-Amplitude Modulation for Non-stationary Time Series Forecasting
May 1, 2026Yingbo Zhou, Yutong Ye, Shuhao Li +5Distribution Shift Time Series Forecasting
Fudan University · Beihang University · Beijing University of Posts and Telecommunications
PAMNet: Cycle-aware Phase-Amplitude Modulation Network for Multivariate Time Series Forecasting
May 1, 2026Yingbo Zhou, Yutong Ye, Zhiwei Ling +5Multivariate Time Series Forecasting Time Series Forecasting
Fudan University · Beihang University · Zhejiang University +1
Explainable Load Forecasting with Covariate-Informed Time Series Foundation Models
Apr 30, 2026Matthias Hertel, Alexandra Nikoltchovska, Sebastian Pütz +3Explainable Time Series Forecasting Time Series Forecasting
Karlsruhe Institute of Technology, Karlsruhe, Germany
Comparative Analysis of Polygon-Based and Global Machine Learning Models for Bus Occupancy Prediction
Apr 30, 2026Daniel Azenkot, Michael Fire, Eran Ben EliaMultivariate Time Series Forecasting Time Series Forecasting
Faculty of Computer and Information Science, University of Ben Gurion, Be’er Sheva, Israel · Department of Geography and Environmental Development, Ben-Gurion, Israel
ITS-Mina: A Harris Hawks Optimization-Based All-MLP Framework with Iterative Refinement and External Attention for Multivariate Time Series Forecasting
Apr 30, 2026Pourya Zamanvaziri, Amirhossein Sadr, Aida Pakniyat +1Multivariate Time Series Forecasting Time Series Forecasting
Department of Computer Science and Engineering, Shahid Beheshti University, Iran · School of Computer Science, Institute for Research in Fundamental Sciences (IPM), Iran
CastFlow: Learning Role-Specialized Agentic Workflows for Time Series Forecasting
Apr 30, 2026Bokai Pan, Mingyue Cheng, Zhiding Liu +6Time Series Forecasting LLM-Based Time Series Forecasting
State Key Laboratory of Cognitive Intelligence, University of Science and Technology of China, Hefei 230026, China
Exploring the Potential of Probabilistic Transformer for Time Series Modeling: A Report on the ST-PT Framework
Apr 29, 2026Zhangzhi Xiong, Haoyi Wu, You Wu +3Transformer Conditional Random Fields
School of Information Science and Technology, ShanghaiTech University
Electricity price forecasting across Norway's five bidding zones in the post-crisis era
Apr 29, 2026My Thi Diem Phan, Trung Tuyen Truong, Hoai Phuong Ha +1Electricity Price Forecasting Time Series Forecasting
Independent researcher · Department of Mathematics, University of Oslo · Department of Computer Science, The Arctic University of Norway +1
Energy-Arena: A Dynamic Benchmark for Operational Energy Forecasting
Apr 27, 2026Max Kleinebrahm, Jonathan Berrisch, Philipp Eiser +11Benchmark Design Time Series Forecasting
Karlsruhe Institute of Technology, Institute for Industrial Production, Karlsruhe, Germany · University of Duisburg-Essen, House of Energy Markets and Finance, Essen, Germany · Karlsruhe Institute of Technology, Institute for Automation and Applied Informatics, Eggenstein-Leopoldshafen, Germany +5
SolarTformer: A Transformer Based Deep Learning Approach for Short Term Solar Power Forecasting
Apr 27, 2026Ankan Basu, Jyotiraditya Roy, Aditya Datta +2Multivariate Time Series Forecasting Time Series Forecasting
Positional Astronomy Centre, India Meteorological Department, Kolkata, India · Department of Computer Science and Engineering, Jadavpur University, Kolkata, India · Department of Computer Science and Engineering (Artificial Intelligence and Machine Learning), Heritage Institute of Technology, Kolkata, India +2

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Hedging Memory Horizons for Non-Stationary Prediction via Online Aggregation

Yutong Wang, Yannig Goude, Qiwei Yao

Department of Statistics, LSE · Électricité de France R&D

Ensemble Learning Time Series Forecasting Non-Stationary Time Series Forecasting Electricity Load Forecasting Adaptive Learning Temporal Distribution Shift

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We study online prediction under distribution shift, where inputs arrive chronologically and outcomes are revealed only after prediction. In this setting, predictors must remain stable in quiet regimes yet adapt when regimes shift, and the right adaptation memory is unknown in advance. We propose MELO (Memory-hedged Exponentially Weighted Least-Squares Online aggregation), a model-agnostic method that hedges across adaptation scales: it wraps any non-anticipating base-predictor pool with exponentially weighted least-squares (EWLS) adaptation experts at multiple forgetting factors, and aggregates raw and EWLS-adapted forecasts with MLpol, a parameter-free online aggregation rule. Under boundedness conditions, we establish deterministic oracle inequalities showing that it competes with both the best raw predictor and the best bounded, time-varying affine combinations of the base predictions, up to a path-length-dependent tracking cost and a sublinear aggregation overhead. We evaluate MELO on French national electricity-load forecasting through the COVID-19 lockdown using no regime indicators, lockdown dates, or policy covariates. MELO reduces overall RMSE by 34.7% relative to base-only MLpol and achieves lower overall RMSE than a TabICL reference supplied with an external COVID policy-response covariate. Moreover, MELO requires only lightweight per-step recursive updates without model retraining.