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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Uncertainty-Aware Transfer Learning for Cross-Building Energy Forecasting: Toward Robust and Scalable District-Level Energy Management
May 28, 2026Shadmehr Zaregarizi, Khashayar YavariUncertainty Quantification Time Series Forecasting
Politecnico di Torino · Turin, Italy
FHRFormer: A Self-Supervised Masked Transformer Framework for Fetal Heart Rate Time-Series Inpainting and Forecasting
May 28, 2026Kjersti Engan, Neel Kanwal, Anita Yeconia +4Time Series Imputation Masked Autoencoders
University of Stavanger, Stavanger, Norway · Haydom Lutheran Hospital, Haydom, Tanzania · Stavanger University Hospital, Stavanger, Norway
Probabilistic bias adjustment of seasonal forecasts using generative machine learning: A case study of Arctic sea ice predictions
May 27, 2026Parsa Gooya, Reinel Sospedra-AlfonsoTime Series Forecasting Probabilistic Forecasting
Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, British Columbia, Canada
Diffusion Model-Based Data Assimilation for Real-World Energy Consumption Forecasting
May 27, 2026Ruoyu Hu, Dahai Yu, Feng Bao +2Time Series Forecasting Data Assimilation
Department of Mathematics, Florida State University, Tallahassee, 32306, Florida, USA · Department of Computer Science, Florida State University, Tallahassee, 32306, Florida, USA · Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, 37831, Tennessee, USA
Online Irregular Multivariate Time Series Forecasting via Uncertainty-Driven Dual-Expert Calibration
May 27, 2026Haonan Wen, Hanyang Chen, Songhe FengIrregular Time-Series Modeling Multivariate Time Series Forecasting
Key Laboratory of Big Data & Artificial Intelligence in Transportation (Beijing Jiaotong University), Ministry of Education School of Computer Science and Technology, Beijing Jiaotong University Beijing, China · School of Computer Science and Technology, Beijing Jiaotong University Beijing, China · Tangshan Research Institute, Beijing Jiaotong University Tangshan, China
GS-FUSE: Granger-Supervised Gated Fusion and Multi-Granularity Alignment for Event-Driven Financial Forecasting
May 27, 2026Yang Zhang, En Chun, Ziyun Mao +2Financial Forecasting Time Series Forecasting
Southwestern University of Finance and Economics Chengdu, China
Decision-focused learning for optimal PV-Battery scheduling
May 27, 2026Joris Depoortere, Hussain Kazmi, Johan DriesenSequential Decision Making Time Series Forecasting
ESAT-Electa KU Leuven, Kasteelpark Arenberg 10, Leuven, 3001, Belgium
Inpainting-Style Conditional Diffusion for Multivariable Time Series Forecasting
May 27, 2026Kourosh Kiani, S. M. MuyeenMultivariate Time Series Forecasting Time Series Forecasting
1Electrical and Computer Engineering, Semnan University, Semnan, Iran · Electrical Engineering Department, Qatar University, Doha, Qatar
Dr-CiK: A Testbed for Foresight-Driven Agents
May 27, 2026Yihong Tang, Andrew Robert Williams, Arjun Ashok +6Time Series Forecasting Forecasting Benchmarks
McGill University · ServiceNow Research · Université de Montréal +3
Transfer Learning using 66 Diseases for Disease Forecasting Applications
May 26, 2026Lauren J Beesley, Alexander C Murph, Dave Osthus +1Multivariate Time Series Forecasting Epidemic Forecasting
Statistics, Los Alamos National Laboratory · Computational Intelligence & Modeling, Los Alamos National Laboratory
Predicting Stock Price Direction on Earnings Announcement Days using Multi-modal Deep Learning
May 25, 2026Manuel Noseda, Nathan Soldati, Marco PainaTime Series Classification Time Series Forecasting
ETH ZÜrich
Electricity Consumption Forecasting: An Approach Using Cooperative Ensemble Learning with SHapley Additive exPlanations
May 25, 2026Eduardo Luiz Alba, Gilson Adamczuk Oliveira, Matheus Henrique Dal Molin Ribeiro +1Multivariate Time Series Forecasting Long-Term Time Series Forecasting
Industrial & Systems Engineering Graduate Program (PPGEPS), Federal University of Technology-Parana (UTFPR), Via do Conhecimento, KM 0l—Fraron, Pato Branco 85503-390, PR, Brazil
Samudra 2: Scaling Ocean Emulators across Resolutions
May 24, 2026Yuan Yuan, Jesse Rusak, Alexander Merose +5Neural Surrogate Modeling Climate Science
Courant Institute School of Mathematics, Computing, and Data Science, New York University, New York, NY, USA · Open Athena AI Foundation, Inc., New York, NY, USA · Program in Atmospheric and Oceanic Sciences, Princeton University, Princeton, NJ, USA
Data-Specific Hyper-Parameter Design: A Paradigm Shift in Reservoir Computing
May 24, 2026G Manjunath, Juan-Pablo Ortega, Alma van der MerweTime Series Forecasting Reservoir Computing
University of Pretoria. Department of Mathematics and Applied Mathematics. Pretoria 0002, South Africa. · Nanyang Technological University. Division of Mathematical Sciences. School of Physical and Mathematical Sciences. Singapore.
AME-TS: Anchored Mixture-of-Experts for Time Series Forecasting
May 24, 2026Rui Wang, Renhao Xue, Ray Razi +2Sparse Mixture-of-Experts Time Series Forecasting
Amazon Web Services
LLM Agent Based Renewable Energy Forecasting Using Edge and IoT Data A Review of Solar Wind Weather and Grid Aware Decision Support
May 24, 2026Pavan Manjunath, Thomas PrueferTime Series Forecasting LLM-Based Time Series Forecasting
Independent Researcher
AION: Next-Generation Tasks and Practical Harness for Time Series
May 24, 2026Tianxiang Zhan, Xiaobao Song, Tong Guan +2Time Series Reasoning Time Series Forecasting
1Griffith University · 2Shenzhen University · 3Zhejiang University
ROAR: Retrieval Opportunity-Aware Refinement for Zero-Shot Time Series Forecasting
May 24, 2026Jinjin Chi, Lei Feng, Yiming Wang +4Zero-Shot Time Series Forecasting Time Series Forecasting
College of Computer Science and Technology, Jilin University, Changchun, China · College of Computing and Data Science, Nanyang Technological University, Singapore
Deep ZakaiJ: Structured Filtering for Jump-Diffusion Time Series Forecasting
May 23, 2026Yan Leng, Thibaut Mastrolia, Hao WangStochastic Differential Equations Latent Dynamics Modeling
University of Texas at Austin · University of California, Berkeley
Assessing the Operational Viability of Foundation Models for Time Series Forecasting
May 23, 2026Kavin Soni, Debanshu Das, Vamshi GuduguntlaZero-Shot Time Series Forecasting Time Series Forecasting
Google, USA
PhenoYieldNet: Learning Crop-Aware Phenological Responses for Multi-Crop Yield Prediction
May 22, 2026Yu Luo, Xiaogang Zhu, Shan Zeng +4Agricultural Remote Sensing Time Series Forecasting
School of Computer Science, The University of Sydney, NSW 2006, Australia · School of Computer Science and Information Technology, Adelaide University, SA 5005, Australia · College of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan, China +2
PrismFlow: Residual Dynamics for Flow Matching in Time-Series Generation
May 22, 2026Junru Zhang, Lang Feng, Jinbo Wang +6Flow Matching Mixture of Experts
Zhejiang University, China · Nanyang Technological University, Singapore · I2R, Agency for Science, Technology and Research (A*STAR), Singapore
Continuity and Ordinality Matter: Constraining Time Series Tokens for Effective Time Series Analysis with Large Language Models
May 22, 2026Musheng Li, Ziying Zhang, Cheng jin +1Time Series Forecasting Time Series Representation Learning
Department of Electronic Engineering Tsinghua University
A Posterior-Predictive Variance Decomposition for Epistemic and Aleatoric Uncertainty in Wind Power Forecasting
May 21, 2026Yinsong Chen, Samson S. Yu, Kashem M. MuttaqiUncertainty Quantification Time Series Forecasting
School of Engineering, Deakin University, Melbourne, VIC 3216, Australia · ARC Training Centre in Energy Technologies for Future Grids, School of Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
Hybrid Kolmogorov-Arnold Network and XGBoost Framework for Week-Ahead Price Forecasting in Australia's National Electricity Market
May 21, 2026Houxuan Zhou, Sriram Prasad, Chenghao Huang +2Electricity Price Forecasting Time Series Forecasting
Department of Data Science and AI, Faculty of IT, Monash University, Australia · School of Electrical Engineering and Computer Science, University of Queensland, Australia · Monash Energy Institute, Monash University, Australia
TimeGuard: Channel-wise Pool Training for Backdoor Defense in Time Series Forecasting
May 21, 2026Quang Duc Nguyen, Siyuan Liang, Yiming Li +2Backdoor Attacks Time Series Forecasting
College of Computing and Data Science, Nanyang Technological University, Singapore.
Reasoning through Verifiable Forecast Actions: Consistency-Grounded RL for Financial LLMs
May 21, 2026Jialin Chen, Aosong Feng, Harshit Verma +7Time Series Reasoning RL for Language Model Reasoning
Yale University · Arizona State University · University of Texas Rio Grande Valley
SURGE: An Event-Centric Social Media Sentiment Time Series Benchmark with Interaction Structure
May 20, 2026Chen Su, Pengsen Cheng, Yuanhe Tian +1Social Media Analysis Multivariate Time Series Forecasting
University of Science and Technology of China · Sichuan University · Zhongguancun Academy
Reviving Error Correction in Modern Deep Time-Series Forecasting
May 20, 2026Minh Hoang Nguyen, Dai Do, Huu Hiep Nguyen +3Long-Term Time Series Forecasting Time Series Forecasting
Deakin Applied AI Initiative, Deakin University, Australia.
PeakFocus: Bridging Peak Localization and Intensity Regression via a Unified Multi-Scale Framework for Electricity Load Forecasting
May 20, 2026Wangzhi Yu, Peng Zhu, Qing Zhao +2Time Series Forecasting Electricity Load Forecasting
School of Computer Science and Technology, Tongji University, Shanghai, China · Big Data Center, State Grid Corporation of China, Beijing, China

May 28, 2026, cs.AIJ/K move · Enter open · S save

Uncertainty-Aware Transfer Learning for Cross-Building Energy Forecasting: Toward Robust and Scalable District-Level Energy Management

Shadmehr Zaregarizi, Khashayar Yavari

Politecnico di Torino · Turin, Italy

Uncertainty Quantification Time Series Forecasting Building Energy Management Cross-Domain Transfer Learning Time Series Transformers Probabilistic Time Series Forecasting

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Scaling data-driven energy forecasting to district level requires models that can be re-used across buildings with minimal target-domain data and honest uncertainty estimates. We present an uncertainty-aware transfer learning (TL) framework for cross-building energy forecasting based on the Temporal Fusion Transformer (TFT), evaluated on a newly released high-resolution real sub-meter dataset: an educational building at Aalborg University, Denmark (source) and the multi-typology NEST building at EMPA, Switzerland (target). We introduce the Transfer Robustness Index (TRI), an architecture-agnostic metric for quantifying generalization quality across domain gaps. A four-strategy layer-freezing ablation shows that Probe-Only fine-tuning, updating only 455 output-layer parameters out of 806K, achieves the best transfer quality (TRI = 3,097), outperforming full fine-tuning and suggesting that TFT encoders learn transferable temporal representations. Monte Carlo Dropout yields a prediction interval coverage probability of 93.2%, close to the nominal 95% target. A data-scarcity analysis further shows monotonic improvement with increasing target-domain data, providing practical guidance for district energy deployment.