Non-Stationary Time Series Forecasting

Follow this topic Ask about this topic

Momentum

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

Jul 13Week of Sep 28

Latest papers 63

All topics

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
Adaptive Oscillatory-State Alignment for Time Series Forecasting
Jun 4, 2026Zhangyao Song, Chaofeng Qu, Chao Zha +3Long-Term Time Series Forecasting Time Series Forecasting
School of Cyber Science and Engineering, Southeast University, Nanjing, China · State Key Laboratory of Blockchain and Data Security, Zhejiang University, Hangzhou, China · School of Information Science and Engineering, Southeast University, Nanjing, China
EpiEvolve: Self-Evolving Agents for Streaming Pandemic Forecasting under Regime Shifts
Jun 3, 2026Yiming Lu, Sihang Zeng, Zhengxu Tang +3Epidemic Forecasting Time Series Forecasting
Emory University · University of Washington
AdaKoop: Efficient Modeling of Nonlinear Dynamics from Nonstationary Data Streams with Koopman Operator Regression
Jun 3, 2026Naoki Chihara, Ren Fujiwara, Yasuko Matsubara +1Koopman Operator Learning Nonlinear System Identification
SANKEN, The University of Osaka Osaka, Japan
Stationarity-Aware Retrieval-Augmented Time Series Forecasting
Jun 2, 2026Shiqiao Zhou, Holger Schöner, Zipeng Wu +3Time Series Forecasting Non-Stationary Time Series Forecasting
University of Birmingham Birmingham, United Kingdom · Siemens AG Munich, Germany
FreqLite: A Lightweight Frequency-Decomposed Linear Model with Adaptive Reversible Normalization for Robust Long-Term Time-Series Forecasting
May 31, 2026Mirza Samad Ahmed Baig, Syeda Anshrah GillaniLong-Term Time Series Forecasting Frequency-Domain Feature Learning
Fandaqah, Al Khobar, Saudi Arabia · Hamdard University, Karachi, Pakistan
STaT: Resolving Shape Distortion in Non-Stationary Time Series via Tri-Modal Synergy
May 25, 2026Hui Cheng, Jinsheng Guo, Zhenhao Weng +2Non-Stationary Time Series Forecasting Multimodal Fusion
Hefei University of Technology Hefei, China
Modeling Dynamic Mixtures of Time-Delay Systems from Streaming Time Series
May 25, 2026Ren Fujiwara, Yasuko Matsubara, Yasushi SakuraiDynamical Systems Online System Identification
SANKEN, The University of Osaka, Japan
Parametric Prior Mapping Framework for Non-stationary Probabilistic Time Series Forecasting
May 22, 2026Jinglin Li, Jun Tan, QI Fang +1Multivariate Time Series Forecasting Non-Stationary Time Series Forecasting
School of Computer Science and Engineering, Central South University, Changsha, China.
Dynamic TMoE: A Drift-Aware Dynamic Mixture of Experts Framework for Non-Stationary Time Series Forecasting
May 20, 2026Jiawen Zhu, Shuhan Liu, Di Weng +1Concept Drift Mixture of Experts
School of Software Technology, Zhejiang University, Ningbo, China · State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China
Deep Learning Surrogates for Emulating Stochastic Climate Tipping Dynamics
May 20, 2026Adeline Hillier, Jennifer Sleeman, Jay Brett +3Neural Surrogate Modeling Multivariate Time Series Forecasting
Johns Hopkins Applied Physics Laboratory Hopkins University · Johns
DeRegiME: Deep Regime Mixtures for Probabilistic Forecasting under Distribution Shift
May 19, 2026Kieran Wood, Stefan Zohren, Stephen J. RobertsDistribution Shift Robustness Time Series Forecasting
Machine Learning Research Group, University of Oxford · Oxford-Man Institute, University of Oxford
L-Drive: Beyond a Single Mapping-Latent Context Drives Time Series Forecasting
May 18, 2026Fan Zhang, Shijun Chen, Hua WangMultivariate Time Series Forecasting Latent Dynamics Modeling
Shandong Technology and Business University, Yantai, Shandong, China · Ludong University, Yantai, Shandong, China
Mechanism Learning: Prototype-Anchored Mechanism Inference for Scientific Forecasting
May 16, 2026Qian Jiang, Liping SunPrototype-Based Learning Non-Stationary Time Series Forecasting
School of Computing · The Australian National University · Canberra, ACT 2601, Australia +3
PULSE: Generative Phase Evolution for Non-Stationary Time Series Forecasting
May 16, 2026Yangyou Liu, Zezhi Shao, Xinyu Chen +3OOD Generalization Time Series Generation
College of Computer Science, Sichuan University, Chengdu, China · Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China · Institute of Artificial Intelligence, University of Central Florida, Orlando, USA +1
Nested Spatio-Temporal Time Series Forecasting
May 15, 2026Yinghao Ai, Yukai Zhou, Ruoxi Jiang +8Non-Stationary Time Series Forecasting Spatiotemporal Forecasting
National Key Laboratory for Novel Software Technology, Nanjing University, China · Shanghai Academy of AI for Science, Shanghai · Department of Computer Science and Technology, Nanjing University +3
SeesawNet: Towards Non-stationary Time Series Forecasting with Balanced Modeling of Common and Specific Dependencies
May 14, 2026Hao Li, Lu Zhang, Liu Chong +3Multivariate Time Series Forecasting Non-Stationary Time Series Forecasting
1Sichuan University · 2Chengdu University of Information Technology · 3McGill University +1
ECTO: Exogenous-Conditioned Temporal Operator for Ultra-Short-Term Wind Power Forecasting
May 12, 2026Cao Yuan, Junjun WangTime Series Forecasting Non-Stationary Time Series Forecasting
Wuhan Polytechnic University, Wuhan, 430048, Hubei, China
LeapTS: Rethinking Time Series Forecasting as Adaptive Multi-Horizon Scheduling
May 11, 2026Sheng Pan, Ming Jin, Bo Du +1Neural Controlled Differential Equations Time Series Forecasting
Griffith University
Yield Curve Forecasting using Machine Learning and Econometrics: A Comparative Analysis
May 11, 2026Aman Singh, Tokunbo Ogunfunmi, Sanjiv DasQuantitative Finance Time Series Forecasting
Department of Electrical and Computer Engineering, Santa Clara University, USA · School of Business, Santa Clara University, USA
STEPS: A Temporal Smooth Error Propagation Solver on the Manifolds for Test-Time Adaptation in Time Series Forecasting
May 8, 2026Jiaqi Liu, Yifan Ouyang, Zhifei Song +2Source-Free Domain Adaptation Test-Time Adaptation
School of Artificial Intelligence and Robotics, Xiamen University Malaysia · S.M.A.R.T. NEXUS Centre of Excellence, Xiamen University Malaysia Sepang, Selangor 43900, Malaysia
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
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
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
Liquid Neural Network Models for Natural Gas Spot Price Time-Series Forecasting
Apr 24, 2026Yiqian Liu, Jiayi Niu, Adam Kelleher +1Liquid Neural Networks Time Series Forecasting
Department of Data Science, Columbia University New York, NY, USA
CAARL: In-Context Learning for Interpretable Co-Evolving Time Series Forecasting
Apr 20, 2026Etienne Tajeuna, Patrick Asante Owusu, Armelle Brun +1Explainable Time Series Forecasting Time Series Forecasting
In-Context Learning Under Regime Change
Apr 18, 2026Carson Dudley, Yutong Bi, Xiaofeng Liu +1Transformer Distribution Shift Detection
Department of Mathematics, University of Michigan · Department of Electrical Engineering and Computer Science, University of Michigan · Michigan Institute for AI and Data in Society, University of Michigan
TimeRFT: Stimulating Generalizable Time Series Forecasting for TSFMs via Reinforcement Finetuning
Apr 18, 2026Siyang Li, Yize Chen, Zijie Zhu +4Time Series Forecasting OOD Generalization
HKUST(GZ) Guangzhou, China · University of Alberta Edmonton, Canada · Alibaba Cloud Guangzhou, China +3
TriTS: Time Series Forecasting from a Multimodal Perspective
Apr 17, 2026Xiang AoLong-Term Time Series Forecasting Cross-Modal Representation Learning
School of Software Engineering, Beijing Jiaotong University Beijing 100044, China
How (Not) to Hybridize Neural and Mechanistic Models for Epidemiological Forecasting
Feb 6, 2026Yiqi Su, Ray Lee, Jiaming Cui +1Epidemic Forecasting Non-Stationary Time Series Forecasting
Department of Computer Science, Virginia Tech, Alexandria, USA.

Oct 6, 2026, cs.LGJ/K move · Enter open · S save

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

Open paper AskPDF arXiv

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.

Momentum

Related topics

Latest papers 63