Multiscale Time-Series Modeling

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Multiscale time-series modeling studies how to represent and predict signals whose patterns unfold over different time spans, from brief events and local fluctuations to cycles and long-term trends. Common approaches use wavelet or frequency decomposition, hierarchical patches and pooling, multi-branch convolutional or Transformer and state-space encoders, and adaptive gates or expert routing to combine scales; some also handle irregular sampling and cross-variable or spatial structure. These methods support forecasting, classification, anomaly detection, imputation, and generation in settings such as sensors, health, climate, traffic, and finance, where missing a scale can obscure useful dynamics. A central challenge is choosing scales that adapt to changing patterns and sampling rates while preserving detail, generalizing across datasets and horizons, and keeping computation and uncertainty reliable.

Latest papers

119 papers18 papers in the last four weeks, up 64% on the four weeks before. 0.1% of all new papers.

MR-ImagenTime: Multi-Resolution Time Series Generation through Dual Image Representations
Mar 30, 2026Xianyong Xu, Yuanjun Zuo, Zhihong Huang +4Time Series Modeling Time Series Forecasting
Department, State Grid Hunan Electric Power Company Limited Research Institute & Hunan Province Engineering Technology Research Center of Electric Power Multimodal Perception and Edge Intelligence, Changsha, Hunan, China. · College of Computer Science, Hunan University, Changsha, Hunan, China.
Dynamic Tokenization via Reinforcement Patching: End-to-end Training and Zero-shot Transfer
Mar 27, 2026Yulun Wu, Sravan Kumar Ankireddy, Samuel Sharpe +4Multiscale Time-Series Modeling Time Series Forecasting
Capital One · University of Texas, Austin
IPatch: A Multi-Resolution Transformer Architecture for Robust Time-Series Forecasting
Mar 25, 2026Aymane Harkati, Moncef Garouani, Olivier Teste +2Robust Time Series Forecasting Time Series Forecasting
CCPS Laboratory, ENSAM, Hassan II University, Casablanca, 20670, Morocco · IRIT, UMR 5505 CNRS, Université Toulouse Capitole, Toulouse, 31000, France · IRIT, UMR 5505 CNRS, Université Toulouse, UT2J, Toulouse, 31000, France
MsFormer: Enabling Robust Predictive Maintenance Services for Industrial Devices
Mar 24, 2026Jiahui Zhou, Dan Li, Ruibing Jin +5Industrial Internet of Things Predictive Maintenance
School of Software Engineering, Sun Yat-Sen University, China · Agency for Science, Technology and Research (A*STAR), Singapore · School of the Art Institute of Chicago, Chicago +1
MRMS-Net and LMRMS-Net: Scalable Multi-Representation Multi-Scale Networks for Time Series Classification
Mar 14, 2026Celal Alagöz, Mehmet Kurnaz, Farhan AadilTime Series Classification Multiscale Time-Series Modeling
Computer Engineering, Sivas Bilim ve Teknoloji Üniversitesi, Sivas, Türkiye
Routing Channel-Patch Dependencies in Time Series Forecasting with Graph Spectral Decomposition
Mar 14, 2026Dongyuan Li, Shun Zheng, Chang Xu +2Multivariate Time Series Forecasting Multiscale Time-Series Modeling
The University of Tokyo · Microsoft Research Asia
Learn Structure, Adapt on the Fly: Multi-Scale Residual Learning and Online Adaptation for Aerial Manipulators
Mar 12, 2026Samaksh Ujjawal, Naveen Sudheer Nair, Shivansh Pratap Singh +3Aerial Robotics Test-Time Adaptation
1Robotics Research Center, IIIT Hyderabad, India. · Department of Computer Science, University of Manchester, UK. · 3Newcastle University, UK.
FreqCycle: A Multi-Scale Time-Frequency Analysis Method for Time Series Forecasting
Mar 10, 2026Boya Zhang, Shuaijie Yin, Huiwen Zhu +1Time Series Forecasting Frequency-Domain Time Series Modeling
Shanghai Jiao Tong University, Shanghai, China
Retrieval-Augmented Multi-scale Framework for County-Level Crop Yield Prediction Across Large Regions
Mar 7, 2026Yiming Sun, Qi Cheng, Licheng Liu +3Crop Yield Prediction Spatiotemporal Forecasting
University of Pittsburgh, Pittsburgh, PA, USA · University of Wisconsin-Madison, Madison, WI, USA · University of Alabama, Tuscaloosa, AL, USA +1
TFWaveFormer: Temporal-Frequency Collaborative Multi-level Wavelet Transformer for Dynamic Link Prediction
Mar 4, 2026Hantong Feng, Yonggang Wu, Duxin Chen +1Time-Frequency Analysis Temporal Link Prediction
School of Cyber Science and Engineering, Southeast University, Nanjing, China · School of Mathematics, Southeast University, Nanjing, China
Role-Aware Conditional Inference for Spatiotemporal Ecosystem Carbon Flux Prediction
Mar 3, 2026Yiming Sun, Runlong Yu, Rongchao Dong +6Spatiotemporal Forecasting Multiscale Time-Series Modeling
University of Pittsburgh, Pittsburgh, PA, USA · University of Alabama, Tuscaloosa, AL, USA · Purdue University, West Lafayette, IN, USA +3
MEBM-Speech: Multi-scale Enhanced BrainMagic for Robust MEG Speech Detection
Feb 27, 2026Li Songyi, Zheng Linze, Liang Jinghua +1Neural Decoding Speech Processing
Speech and Hearing Research Center, School of Intelligence Science and Technology, Peking University, Beijing, China 100871 · Center for BioMed-X Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China 100871
SDMixer: Sparse Dual-Mixer for Time Series Forecasting
Feb 27, 2026Xiang AoMultivariate Time Series Forecasting Time Series Forecasting
School of Software Engineering, Beijing Jiaotong University, Beijing, China
WaveSSM: Multiscale State-Space Models for Non-stationary Signal Attention
Feb 25, 2026Ruben Solozabal, Velibor Bojkovic, Hilal Alquabeh +3State Space Models Multiscale Time-Series Modeling
MBZUAI · RIKEN AIP
Learning Recursive Multi-Scale Representations for Irregular Multivariate Time Series Forecasting
Feb 25, 2026Boyuan Li, Zhen Liu, Yicheng Luo +1Irregular Time-Series Modeling Multivariate Time Series Forecasting
School of Computer Science and Engineering, South China University of Technology
CGSTA: Cross-Scale Graph Contrast with Stability-Aware Alignment for Multivariate Time-Series Anomaly Detection
Feb 24, 2026Zhongpeng Qi, Jun Zhang, Wei Li +1Time-Series Anomaly Detection Graph Contrastive Learning
Dalian Maritime University, Dalian, China · Harbin Engineering University, Harbin, China
M3S-Net: Multimodal Feature Fusion Network Based on Multi-scale Data for Ultra-short-term PV Power Forecasting
Feb 23, 2026Penghui Niu, Taotao Cai, Suqi Zhang +4Solar Power Forecasting Multimodal Fusion
School of Artificial Intelligence, Hebei University of Technology, Tianjin 300401, China · University of Southern Queensland, Toowoomba 487-535, Australia · School of Information Engineering, Tianjin University of Commerce, Tianjin 300134, China +3
Stable Long-Horizon Spatiotemporal Prediction on Meshes Using Latent Multiscale Recurrent Graph Neural Networks
Feb 20, 2026Lionel Salesses, Larbi Arbaoui, Tariq Benamara +2Spatiotemporal Forecasting Neural Surrogate Modeling
Cenaero, Gosselies, Belgium
HPMixer: Hierarchical Patching for Multivariate Time Series Forecasting
Feb 18, 2026Jung Min Choi, Vijaya Krishna Yalavarthi, Lars Schmidt-ThiemeMultivariate Time Series Forecasting Long-Term Time Series Forecasting
ISMLL, University of Hildesheim
SEMixer: Semantics Enhanced MLP-Mixer for Multiscale Mixing and Long-term Time Series Forecasting
Feb 18, 2026Xu Zhang, Qitong Wang, Peng Wang +1Long-Term Time Series Forecasting Multi-Scale Feature Fusion
Shanghai Key Laboratory of Data Science, College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China · Harvard University, Cambridge, Massachusetts, United States
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.
Spectral Text Fusion: A Frequency-Aware Approach to Multimodal Time-Series Forecasting
Feb 2, 2026Huu Hiep Nguyen, Minh Hoang Nguyen, Dung Nguyen +1Multivariate Time Series Forecasting Frequency-Domain Time Series Modeling
Applied Artificial Intelligence Initiative Deakin University Geelong, Australia
HieraMix: A Hierarchical MLP-Mixer for Large-Scale Traffic Forecasting
Nov 26, 2025Yongyao Wang, Xie Yu, Jingyuan Wang +2Intelligent Transportation Systems Spatiotemporal Forecasting
1State Key Laboratory of Complex & Critical Software Environment (SKLCCSE) · School of Computer Science and Engineering, Beihang University, Beijing, China · 3MOE Engineering Research Center of Advanced Computer Application Technology, Beihang University, China
Kairos: Toward Adaptive and Parameter-Efficient Time Series Foundation Models
Sep 30, 2025Kun Feng, Shaocheng Lan, Yuchen Fang +6Rotary Positional Embeddings Zero-Shot Time Series Forecasting
School of Information Science and Technology, ShanghaiTech University, Shanghai, China · Ant Group, Shanghai, China
User Trajectory Prediction Unifying Global and Local Temporal Information
Aug 4, 2025Wei Hao, Bin Chong, Ronghua Ji +1Human Trajectory Prediction Trajectory Prediction
College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China · National Engineering Laboratory for Big Data Analysis and Applications, Peking University, Beijing 100871, China
DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting
Aug 3, 2025Haonan Yang, Jianchao Tang, Zhuo Li +1Time Series Forecasting Multi-Scale Feature Fusion
National University of Defense Technology, Changsha, Hunan, China
Learning Intrinsic Water-Quality Dynamics with Rainfall for Data-Driven Forecasting
Aug 1, 2025Ziqi Wang, Hailiang Zhao, Cheng Bao +3Multivariate Time Series Forecasting Time Series Forecasting
Zhejiang University
FISHER: A Foundation Model for Multi-Modal Industrial Signal Comprehensive Representation
Jul 22, 2025Pingyi Fan, Anbai Jiang, Shuwei Zhang +9Representation Learning Self-Supervised Time Series Representation Learning
Department of Electronic Engineering, Tsinghua University, Beijing, 100084, P. R. China · Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, P. R. China · Huakong AI Plus Company Limited, Beijing, 100084, P. R. China +1
Fast, Interpretable, and Deterministic Time Series Classification With a Bag-of-Receptive-Fields
Nov 29, 2023Francesco Spinnato, Riccardo Guidotti, Anna Monreale +1Time Series Classification Interpretable ML
Scuola Normale Superiore, Pisa, Italy · University of Pisa, Pisa, Italy · ISTI-CNR, Pisa, Italy

Mar 30, 2026J/K move · Enter open · S save

MR-ImagenTime: Multi-Resolution Time Series Generation through Dual Image Representations

Xianyong Xu, Yuanjun Zuo, Zhihong Huang, Yihan Qin+3

Department, State Grid Hunan Electric Power Company Limited Research Institute & Hunan Province Engineering Technology Research Center of Electric Power Multimodal Perception and Edge Intelligence, Changsha, Hunan, China. · College of Computer Science, Hunan University, Changsha, Hunan, China.

Time Series Modeling Time Series Forecasting Multiscale Time-Series Modeling Time Series Generation Conditional Diffusion Models

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Time series forecasting is vital across many domains, yet existing models struggle with fixed-length inputs and inadequate multi-scale modeling. We propose MR-CDM, a framework combining hierarchical multi-resolution trend decomposition, an adaptive embedding mechanism for variable-length inputs, and a multi-scale conditional diffusion process. Evaluations on four real-world datasets demonstrate that MR-CDM significantly outperforms state-of-the-art baselines (e.g., CSDI, Informer), reducing MAE and RMSE by approximately 6-10 to a certain degree.