Non-Stationary Time Series Forecasting

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4 papers in the last four weeks, up 33% on the four weeks before. 0.0% of all new papers.

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Are We Really Benchmarking Forecasting Models? The Impact of Preprocessing on Time Series Performance
Oct 6, 2026Guilherme Afonso Galindo Padilha, Paulo Salgado Gomes de Mattos Neto, Rafael Menelau Oliveira e CruzTime Series Forecasting Forecasting Benchmarks
LIVIA, Department of Software and IT Engineering École de technologie supérieure (ÉTS) Montreal, QC, Canada · Center for Informatics (CIn) Universidade Federal de Pernambuco (UFPE) Recife, PE, Brazil
Retrieval Is Not Enough: Refreshing Memory for Frozen Time-Series Forecasters
Oct 6, 2026Chao He, Jianyu Xu, Xinyi Guo +5Non-Stationary Time Series Forecasting Retrieval-Augmented Time Series Forecasting
Aberdeen Institute of Data Science and Artificial Intelligence South China Normal University Foshan, China · School of Artificial Intelligence South China Normal University Foshan, China · Faculty of Humanities and Arts Macau University of Science and Technology Macau, China
Pseudo-Label-Triggered Retraining from Forecast Errors for Online Time Series Forecasting
Sep 30, 2026Yeryeong Kwak, Yoo-Min Jung, Jonghun ParkMultivariate Time Series Forecasting Time Series Forecasting
Seoul National University Seoul, Republic of Korea
Predicting Delayed Train Trajectories on the Dutch Railway Network: Explainable AI Evaluation of Topological, Operational and Weather Features with Tree Based Ensemble Methods
Sep 28, 2026Jia Long Bao, Ali Mohammed Mansoor Alsahag, Seyed Sahand Mohammadi ZiabariExplainable Time Series Forecasting Time Series Forecasting
Beyond Average Error through Oracle-Informed Stress Tests for Time-Series Forecasting
Sep 19, 2026Xu Lin, Runheng Zuo, Shengxuan Xu +3Multivariate Time Series Forecasting Time Series Forecasting
Tsinghua University
VertiFuseX: Generalizable Financial Forecasting via Multi-Stream Temporal Fusion
Sep 14, 2026Aashish Bohra, Vivek VijayFinancial Forecasting Non-Stationary Time Series Forecasting
Department of Computer Science and Engineering, Indian Institute of Technology Jodhpur, Jodhpur, Rajasthan, India · Department of Mathematics, Indian Institute of Technology Jodhpur, Jodhour, Inida
Compositional Spectral Prompts for LLM-based Online Time Series Forecasting
Sep 2, 2026Seungyoon Choi, Hyunchul Kim, Jae-Gil Lee +1Time Series Forecasting LLM-Based Time Series Forecasting
KAIST Daejeon, Republic of Korea
Regime-Gated Residual Mixture-of-Experts for Cross-Sectional Volatility Forecasting
Aug 12, 2026Junyi Ye, Gargi Vijay BordeQuantitative Finance Non-Stationary Time Series Forecasting
School of Computing, Montclair State University · Montclair, New Jersey, USA
AirFlow: Context Preserving and Multi-Rate State Modeling for Air Quality Forecasting
Aug 10, 2026Fan Yang, Nan Chen, Yijie Dong +2Multivariate Time Series Forecasting Air Quality Prediction
School of Software Technology, Zhejiang University Hangzhou, Zhejiang 310000, China
End-to-End Neural Decomposition with Koopman Operators for Time-Series Forecasting
Aug 9, 2026De-Yan Lu, Xugang Lu, Yu Tsao +1Koopman Operator Learning Time Series Forecasting
Graduate Institute of Communication Engineering, National Taiwan University, Taipei, Taiwan · National Institute of Information and Communications Technology, Kyoto, Japan · Research Center for Information Technology Innovation, Academic Sinica, Taipei, Taiwan
QFCQT: A Chaotically Gated Quantformer Framework for Volatile Time-Series Forecasting
Aug 7, 2026Junkai Lin, Siqi Hou, Raymond LeeMultivariate Time Series Forecasting Time Series Forecasting
Faculty of Science and Technology, Beijing Normal-Hong Kong Baptist University, Zhuhai, China · Guangdong Provincial Key Lab of Interdisciplinary Research and Application for Data Science (BNBU), Zhuhai, China
EpiFlow: A framework for improving the utility of wastewater signals for disease forecasting
Aug 7, 2026Aniruddha Adiga, Jingyuan Chou, Gursharn Kaur +8Epidemic Forecasting Probabilistic Forecasting
Biocomplexity Institute, University of Virginia · Department of Computer Science, University of Virginia · Virginia Department of Health +3
Adaptive Multi-Scale Forecasting and Gate-Localized Conformal Prediction for Multivariate Nonstationary Time Series
Jul 25, 2026Ziling Ma, Junshu Jiang, Ángel López-Oriona +2Multivariate Time Series Forecasting Conformal Prediction
Statistics Department, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia · NeuroAI Laboratory, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia
Black-Mamba: Biologically-Inspired Leaky Accumulation for Conceptual Knowledge under Distribution Drift
Jul 21, 2026Giuseppe Soriano, Nicola Tonellotto, Alberto GottaTest-Time Adaptation Concept Drift
University of Pisa National Research Council (CNR) Pisa, Italy · University of Pisa Pisa, Italy · National Research Council (CNR) Pisa, Italy
Long-Memory Reservoir Computing for Data-Scarce Dengue Forecasting
Jul 13, 2026Rahul Goswami, Shinjini Paul, Palash Ghosh +1Epidemic Forecasting Reservoir Computing
Department of Mathematics, Indian Institute of Technology Guwahati, India · SAFIR, Sorbonne University Abu Dhabi, United Arab Emirates · Leiden University, Leiden, South Holland, Netherlands +1
GatedLinear: Adaptive Routing of Complementary Linear Bases for Time Series Forecasting
Jul 10, 2026Qitai Tan, Ruiwen Gu, Yilin Su +3Mixture of Experts Time Series Forecasting
Shenzhen Key Laboratory of Ubiquitous Data Enabling · Shenzhen International Graduate School, Tsinghua University
PARA-PV: Physics-Aware Retrieval-Augmented PV Prediction Based on Frozen Foundation Model and Distribution Shift Correction
Jul 9, 2026Hang Fan, Weican Liu, Ying Lu +3Time Series Forecasting Non-Stationary Time Series Forecasting
School of Economics and Management, North China Electric Power University, 102206, Beijing, China · School of Electrical and Electronic Engineering, Nanyang Technological University, 639798, 50 Nanyang Avenue, Singapore · Department of Electrical Engineering, Tsinghua University, 100084, Beijing, China
Evaluating Time Series Foundation Models for Electricity Price Forecasting: Contamination Risk, Distributional Shifts, and Covariate Dependence
Jul 2, 2026Zhenghua Pan, Ahmed Aziz EzzatZero-Shot Time Series Forecasting Electricity Price Forecasting
Department of Industrial & Systems Engineering, Rutgers, The State University of New Jersey, USA.
Neural Network-Based Estimation of Time-Dependent Parameters in AR(p) Processes
Jul 1, 2026Agnieszka Kopeć, Paweł Przybyłowicz, Martyna WiącekParameter Estimation Probabilistic Forecasting
StateFlow: Dual-State Recurrent Modeling for Long-Horizon Time Series Forecasting
Jun 30, 2026Haroon Gharwi, Yue Dai, Kai ShuMultivariate Time Series Forecasting Long-Term Time Series Forecasting
Department of Computer Science, Illinois Institute of Technology, Chicago, IL, USA · Department of Computer Science, Emory University, Atlanta, GA, USA
Adaptive Financial Transformer with Regime-Gated Attention for Stock Return Prediction
Jun 28, 2026Dishan SarkarMultivariate Time Series Forecasting Time Series Forecasting
Department of Artificial Intelligence and Machine Learning Birla Institute of Technology, Mesra Ranchi, India
When Prices Double in a Week: Forecasting of Agricultural Volatility in Import-Isolated Markets
Jun 28, 2026Ranuga Weerasekara, Heshan Nethmina, Manuja Ranathunga +6Time Series Forecasting Non-Stationary Time Series Forecasting
Dept. of Computer Science & Engineering, University of Moratuwa, Sri Lanka.
TA-SparseMG: Trend-Aware Sparse Forecasting via Multi-Scale Gating for Long-Term Time Series
Jun 26, 2026Wenchao Liu, Hongbing Wang, Youji Zhu +2Long-Term Time Series Forecasting Non-Stationary Time Series Forecasting
School of Mathematical Sciences, Guizhou Normal University, Guiyang 550025, China. · School of Big Data and Computer Science, Guizhou Normal University, Guiyang 550025, China.
Towards Continuous Power Forecasting: Practical Continual Learning for Real-World Energy Systems in Nonstationary Time Series
Jun 23, 2026Yujiang He, Frederic Uhrweiller, Bernhard SickContinual Learning Time Series Forecasting
Intelligent Embedded Systems, University of Kassel, 34121 Kassel, Germany
RAVEN: A Regime-Aware Variable-context Expert Network for Financial Time Series Forecasting
Jun 23, 2026Cheng He, Zhenyu Guan, Xijie Liang +6Financial Forecasting Time Series Forecasting
University of Science and Technology of China, China · Shanghai Black Wing Asset Management Co., Ltd., China · College of Sciences, Shanghai University, China +2
Spectral Retrieval-Augmented Time-Series Forecasting
Jun 17, 2026Huu Hiep Nguyen, Minh Hoang Nguyen, Dung Nguyen +1Non-Stationary Time Series Forecasting Retrieval-Augmented Time Series Forecasting
Applied Artificial Intelligence Initiative Deakin University Geelong, Australia
Delta-Based Target Reformulation for Short-Term Electricity Load Forecasting Using LSTM and Transformer Models
Jun 16, 2026Vansh BansalTime Series Forecasting Non-Stationary Time Series Forecasting
Semantics-Enhanced Retrieval-Augmented Time Series Forecasting
Jun 12, 2026Shiqiao Zhou, Zipeng Wu, Holger Schöner +3Time Series Forecasting Non-Stationary Time Series Forecasting
School of Computer Science, University of Birmingham, Birmingham, United Kingdom · School of Mathematics, University of Birmingham, Birmingham, United Kingdom · Siemens AG, Munich, Germany +1
Does Normalization Choice Matter for Causal Large Time-Series Models?
Jun 8, 2026Samy-Melwan Vilhes, Gilles Gasso, Mokhtar Z AlayaTime Series Forecasting Non-Stationary Time Series Forecasting
LMAC · INSA Rouen Normandie, Univ Rouen Normandie Univ, LITIS UR4108, F-76000 Rouen, France · Univ de Technologie de Compi`egne, LMAC EA 222, F-60203 Compi`egne, France
InA-Probe: Instruction-Aware Active Probing for Time Series Forecasting with LLMs
Jun 7, 2026Peiliang Gong, Emadeldeen Eldele, Chenyu Liu +8Zero-Shot Time Series Forecasting Time Series Forecasting
College of Computing and Data Science, Nanyang Technological University, Singapore · Department of Computer Science, Khalifa University, UAE · Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China +1

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Are We Really Benchmarking Forecasting Models? The Impact of Preprocessing on Time Series Performance

Guilherme Afonso Galindo Padilha, Paulo Salgado Gomes de Mattos Neto, Rafael Menelau Oliveira e Cruz

LIVIA, Department of Software and IT Engineering École de technologie supérieure (ÉTS) Montreal, QC, Canada · Center for Informatics (CIn) Universidade Federal de Pernambuco (UFPE) Recife, PE, Brazil

Time Series Forecasting Forecasting Benchmarks Non-Stationary Time Series Forecasting

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While established literature underscores the pivotal role of preprocessing in forecasting accuracy, this stage remains largely overlooked in current research. Modern benchmarks typically resort to simple scaling, failing to account for critical transformations required to address nonstationarity, such as differencing. This omission creates a significant structural preprocessing bias that favors models with built-in data treatments while obscuring the true potential of simpler architectures. We study this effect through a preprocessing-aware benchmark that evaluates 11 forecasting models across 16 reversible preprocessing pipelines on 29,000 M4 time series. Our results identify preprocessing as a key driver of forecasting performance. Optimizing preprocessing per series yields gains of approximately 27% to 87% across all evaluated models, with architectures lacking internalized preprocessing experiencing the most substantial improvements. This allows simpler architectures to become highly competitive with complex, state-of-the-art models in modern forecasting benchmarks. All resources and experimental results from this benchmark are stored in a comprehensive metadataset to support future metalearning tasks.

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