Time-series forecasting
This page was last updated on 2026-02-02 06:32:29 UTC
Manually curated articles on Time-series forecasting
| Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index | View recommendations |
|---|---|---|---|---|---|---|---|
| visibility_off | A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection | Ming Jin, Huan Yee Koh, Qingsong Wen, Daniele Zambon, C. Alippi, G. I. Webb, Irwin King, Shirui Pan | 2023-07-07 | IEEE Transactions on Pattern Analysis and Machine Intelligence | 354 | 54 | open_in_new |
| visibility_off | Graph-Guided Network for Irregularly Sampled Multivariate Time Series | Xiang Zhang, M. Zeman, Theodoros Tsiligkaridis, M. Zitnik | 2021-10-11 | ArXiv, International Conference on Learning Representations | 148 | 59 | open_in_new |
| visibility_off | Taming Local Effects in Graph-based Spatiotemporal Forecasting | Andrea Cini, Ivan Marisca, Daniele Zambon, C. Alippi | 2023-02-08 | Neural Information Processing Systems, ArXiv | 48 | 54 | open_in_new |
| visibility_off | Sparse Graph Learning from Spatiotemporal Time Series | Andrea Cini, Daniele Zambon, C. Alippi | 2022-05-26 | J. Mach. Learn. Res., Journal of machine learning research | 29 | 54 | open_in_new |
| visibility_off | Graph Deep Learning for Time Series Forecasting | Andrea Cini, Ivan Marisca, Daniele Zambon, C. Alippi | 2023-10-24 | ACM Computing Surveys | 33 | 54 | open_in_new |
| visibility_off | Large Language Models Are Zero-Shot Time Series Forecasters | Nate Gruver, Marc Finzi, Shikai Qiu, Andrew Gordon Wilson | 2023-10-11 | Neural Information Processing Systems, ArXiv | 594 | 18 | open_in_new |
| visibility_off | Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces | Chloe Wang, Oleksii Tsepa, Jun Ma, Bo Wang | 2024-02-01 | ArXiv, arXiv.org | 149 | 7 | open_in_new |
| visibility_off | A decoder-only foundation model for time-series forecasting | Abhimanyu Das, Weihao Kong, Rajat Sen, Yichen Zhou | 2023-10-14 | International Conference on Machine Learning, ArXiv | 468 | 15 | open_in_new |
| visibility_off | Unified Training of Universal Time Series Forecasting Transformers | Gerald Woo, Chenghao Liu, Akshat Kumar, Caiming Xiong, Silvio Savarese, Doyen Sahoo | 2024-02-04 | International Conference on Machine Learning, ArXiv | 408 | 34 | open_in_new |
| visibility_off | Time-LLM: Time Series Forecasting by Reprogramming Large Language Models | Ming Jin, Shiyu Wang, Lintao Ma, Zhixuan Chu, James Y. Zhang, X. Shi, Pin-Yu Chen, Yuxuan Liang, Yuan-Fang Li, Shirui Pan, Qingsong Wen | 2023-10-03 | ArXiv, International Conference on Learning Representations | 731 | 14 | open_in_new |
| visibility_off | Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series | Vijay Ekambaram, Arindam Jati, Nam H. Nguyen, Pankaj Dayama, Chandra Reddy, Wesley M. Gifford, Jayant Kalagnanam | 2024-01-08 | Neural Information Processing Systems, ArXiv | 91 | 5 | open_in_new |
| visibility_off | Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency | Xiang Zhang, Ziyuan Zhao, Theodoros Tsiligkaridis, M. Zitnik | 2022-06-17 | Neural Information Processing Systems, ArXiv | 414 | 59 | open_in_new |
| visibility_off | Domain Adaptation for Time Series Under Feature and Label Shifts | Huan He, Owen Queen, Teddy Koker, Consuelo Cuevas, Theodoros Tsiligkaridis, M. Zitnik | 2023-02-06 | DBLP, ArXiv | 106 | 59 | open_in_new |
| visibility_off | AZ-whiteness test: a test for signal uncorrelation on spatio-temporal graphs | Daniele Zambon, C. Alippi | None | DBLP | 8 | 54 | open_in_new |
| visibility_off | Graph state-space models | Daniele Zambon, Andrea Cini, L. Livi, C. Alippi | 2023-01-04 | ArXiv, arXiv.org | 8 | 54 | open_in_new |
| visibility_off | UniTS: A Unified Multi-Task Time Series Model | Shanghua Gao, Teddy Koker, Owen Queen, Thomas Hartvigsen, Theodoros Tsiligkaridis, M. Zitnik | 2024-02-29 | Neural Information Processing Systems, Advances in Neural Information Processing Systems 37 | 67 | 59 | open_in_new |
| Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index | View recommendations |
Recommended articles on Time-series forecasting
| Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |
|---|---|---|---|---|---|---|
| visibility_off | TimePerceiver: An Encoder-Decoder Framework for Generalized Time-Series Forecasting | Jaebin Lee, Hankook Lee | 2025-12-27 | ArXiv | 0 | 0 |
| visibility_off | MoHETS: Long-term Time Series Forecasting with Mixture-of-Heterogeneous-Experts | Evandro S. Ortigossa, Guy Lutsker, Eran Segal | 2026-01-29 | ArXiv | 0 | 4 |
| visibility_off | Seg-MoE: Multi-Resolution Segment-wise Mixture-of-Experts for Time Series Forecasting Transformers | Evandro S. Ortigossa, Eran Segal | 2026-01-29 | ArXiv | 0 | 4 |
| visibility_off | Patch-Level Tokenization with CNN Encoders and Attention for Improved Transformer Time-Series Forecasting | Saurish Nagrath, Saroj Kumar Panigrahy | 2026-01-18 | ArXiv | 0 | 12 |
| visibility_off | KALFormer: Knowledge-augmented attention learning for long-term time series forecasting with transformer | Xing Dong, Qianwei Yang, Wenbo Cheng, Yun Zhang | 2026-01-05 | PLOS One | 0 | 1 |
| visibility_off | DynaSTy: A Framework for SpatioTemporal Node Attribute Prediction in Dynamic Graphs | Namrata Banerji, Tanya Y. Berger-Wolf | 2026-01-08 | ArXiv | 0 | 5 |
| visibility_off | LLM-WPFNet: A Dual-Modality Fusion Network for Large Language Model-Empowered Wind Power Forecasting | Xuwen Zheng, Yongliang Luo, Yahui Shan | 2025-12-17 | Symmetry | 0 | 0 |
| visibility_off | XLinear: A Lightweight and Accurate MLP-Based Model for Long-Term Time Series Forecasting with Exogenous Inputs | Xinyang Chen, Huidong Jin, Yu Huang, Zaiwen Feng | 2026-01-14 | ArXiv | 0 | 0 |
| visibility_off | In-Context and Few-Shots Learning for Forecasting Time Series Data based on Large Language Models | Saroj Gopali, Bipin Chhetri, Deepika Giri, Sima Siami‐Namini, A. Namin | 2025-12-08 | ArXiv | 0 | 25 |
| visibility_off | What Matters in Deep Learning for Time Series Forecasting? | Valentina Moretti, Andrea Cini, Ivan Marisca, C. Alippi | 2025-12-27 | ArXiv | 0 | 54 |
| visibility_off | PiXTime: A Model for Federated Time Series Forecasting with Heterogeneous Data Structures Across Nodes | Yiming Zhou, Mingyue Cheng, Hao Wang, Enhong Chen | 2026-01-09 | ArXiv | 0 | 16 |
| visibility_off | TwinFormer: A Dual-Level Transformer for Long-Sequence Time-Series Forecasting | Mahima Kumavat, Aditya Maheshwari | 2025-12-13 | ArXiv | 0 | 0 |
| visibility_off | DeMa: Dual-Path Delay-Aware Mamba for Efficient Multivariate Time Series Analysis | Rui An, Haohao Qu, Wenqi Fan, Xuequn Shang, Qing Li | 2026-01-09 | ArXiv | 0 | 12 |
| visibility_off | Time series forecasting with Hahn Kolmogorov-Arnold networks | Md Zahidul, Hasan A. Ben, Hamza Nizar Bouguila | 2026-01-25 | ArXiv | 0 | 0 |
| visibility_off | Learning to Factorize and Adapt: A Versatile Approach Toward Universal Spatio-Temporal Foundation Models | Siru Zhong, Junjie Qiu, Yangyu Wu, Yiqiu Liu, Yuanpeng He, Zhongwen Rao, Bin Yang, Chenjuan Guo, Hao Xu, Yuxuan Liang | 2026-01-17 | ArXiv | 0 | 38 |
| visibility_off | A Unified Shape-Aware Foundation Model for Time Series Classification | Zhen Liu, Yucheng Wang, Boyuan Li, Junhao Zheng, Emadeldeen Eldele, Min Wu, Qianli Ma | 2026-01-10 | ArXiv | 0 | 14 |
| visibility_off | FreqFormer: Frequency-Aware Multi-Scale Transformer with Gated Temporal Fusion for Robust Time Series Forecasting | Yixin Liang, Jinbao Hong, Qining Wu, Wanting Liu, Zile Dong | 2025-12-19 | 2025 22nd International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) | 0 | 0 |
| visibility_off | CPiRi: Channel Permutation-Invariant Relational Interaction for Multivariate Time Series Forecasting | Jiyuan Xu, Wenyu Zhang, Xin Jing, Shuai Chen, Shuai Zhang, Jiahao Nie | 2026-01-28 | ArXiv | 0 | 32 |
| visibility_off | Periodicity Variations Modelling Based on 2D Multi‐Scale Patch for Multivariate Time Series Forecasting Using Improved MLP and Depthwise Separable Convolution | Yachuan Wang, Mi Wen, Dongyang Li, Jigang Wang | 2025-12-08 | Expert Systems | 0 | 0 |
| visibility_off | Time Series Foundation Models for Process Model Forecasting | Yongbo Yu, Jari Peeperkorn, Johannes De Smedt, Jochen De Weerdt | 2025-12-08 | ArXiv | 0 | 31 |
| visibility_off | An Exploratory Study to Repurpose LLMs to a Unified Architecture for Time Series Classification | Hansen He, Shuheng Li | 2026-01-15 | ArXiv | 0 | 0 |
| visibility_off | A lightweight Spatial-Temporal Graph Neural Network for Long-term Time Series Forecasting | H. Moges, Deshendran Moodley | 2025-12-19 | ArXiv | 0 | 14 |
| visibility_off | Enhancing Zero-Shot Time Series Forecasting in Off-the-Shelf LLMs via Noise Injection | Xingyou Yin, Ceyao Zhang, Min Hu, Kai Chen | 2025-12-23 | ArXiv | 0 | 0 |
| visibility_off | Spatiotemporal memory probabilistic sparse transformer for traffic flow prediction | Linlong Chen, Qing-Hua Wu | 2025-12-26 | Journal of King Saud University Computer and Information Sciences | 0 | 4 |
| visibility_off | ACFormer: Mitigating Non-linearity with Auto Convolutional Encoder for Time Series Forecasting | Gawon Lee, Hanbyeol Park, Minseop Kim, Dohee Kim, Hyerim Bae | 2026-01-28 | ArXiv | 0 | 5 |
| visibility_off | Pstanet: patchwise spectro-temporal analytic network for multivariate long-sequence time series forecasting | Chunru Dong, Wei Luo, Qiang Hua, Yong Zhang, Fen Zhang | 2026-01-01 | International Journal of Machine Learning and Cybernetics | 0 | 4 |
| visibility_off | TSAformer: A Traffic Flow Prediction Model Based on Cross-Dimensional Dependency Capture | Haoning Lv, Xi Chen, Weijie Xiu | 2026-01-04 | Electronics | 0 | 0 |
| visibility_off | Enhancing Large Language Models for Time-Series Forecasting via Vector-Injected In-Context Learning | Jianqi Zhang, Jingyao Wang, Wenwen Qiang, Fanjiang Xu, Changwen Zheng | 2026-01-12 | ArXiv | 0 | 12 |
| visibility_off | One-Shot Price Forecasting with Covariate-Guided Experts under Privacy Constraints | Ren He, Yinliang Xu, Jinfeng Wang, Jeremy Watson, Jian Song | 2026-01-17 | ArXiv | 0 | 1 |
| visibility_off | Adaptive Normalization Mamba with Multi Scale Trend Decomposition and Patch MoE Encoding | MinCheol Jeon | 2025-12-07 | ArXiv | 0 | 0 |
| visibility_off | MODE: Efficient Time Series Prediction with Mamba Enhanced by Low-Rank Neural ODEs | Xingsheng Chen, Regina Zhang, Bo Gao, Xingwei He, Xiaofeng Liu, Pietro Lio, Kwok-Yan Lam, S. Yiu | 2026-01-01 | ArXiv | 0 | 6 |
| visibility_off | Station-Aware Patch-Gated Temporal Transformer for Multihorizon Forecasting in Smart City Applications | Raeed Al-sabri, Saad Hameed, M. R. Alfarra, Mohamed Abdallah, Ala I. Al-Fuqaha | 2025-12-14 | 2025 Computing, Communications and IoT Applications (ComComAp) | 0 | 30 |
| visibility_off | A Uncertainty-Calibrated Transformer for Long-Horizon Forecasting with Missing and Irregular Observations | Joseph Hernandez, Barbara Hall | 2025-12-30 | Frontiers in Artificial Intelligence Research | 0 | 0 |
| visibility_off | LLM-Empowered Time Series Prediction with Cross-Modal Fusion | Xingheng Wan, Meng Liu, Yuzhe Li, Tian Yang, Shuhao Zhang, Zhikui Chen | 2025-12-15 | 2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) | 0 | 2 |
| visibility_off | vLinear: A Powerful Linear Model for Multivariate Time Series Forecasting | Wenzhen Yue, Ruohao Guo, Ji Shi, Zihan Hao, Shiyu Hu, Xianghua Ying | 2026-01-20 | ArXiv | 0 | 6 |
| visibility_off | DB2-TransF: All You Need Is Learnable Daubechies Wavelets for Time Series Forecasting | Moulik Gupta, A. Tripathi | 2025-12-10 | ArXiv | 0 | 10 |
| visibility_off | Multi-Modal Time Series Prediction via Mixture of Modulated Experts | Lige Zhang, Ali Maatouk, Jialin Chen, L. Tassiulas, Rex Ying | 2026-01-29 | ArXiv | 0 | 13 |
| visibility_off | FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecasting | Xingjian Wu, Hanyin Cheng, Xiangfei Qiu, Zhengyu Li, Jilin Hu, Chenjuan Guo, Bin Yang | 2025-12-16 | ArXiv | 1 | 38 |
| visibility_off | WinStat: A Family of Trainable Positional Encodings for Transformers in Time Series Forecasting | Cristhian Moya-Mota, Ignacio Aguilera-Martos, Diego García-Gil, Julián Luengo | 2025-12-29 | Machine Learning and Knowledge Extraction | 0 | 10 |
| visibility_off | Dual-Prototype Disentanglement: A Context-Aware Enhancement Framework for Time Series Forecasting | Haonan Yang, Jianchao Tang, Zhuo Li | 2026-01-23 | ArXiv | 0 | 0 |
| visibility_off | PatchFormer: A Patch-Based Time Series Foundation Model with Hierarchical Masked Reconstruction and Cross-Domain Transfer Learning for Zero-Shot Multi-Horizon Forecasting | Olaf Yunus Laitinen Imanov, Derya Umut Kulali, Taner Yilmaz | 2026-01-28 | ArXiv | 0 | 0 |
| visibility_off | A Comparative Study of Adaptation Strategies for Time Series Foundation Models in Anomaly Detection | Miseon Park, Kijung Yoon | 2026-01-01 | ArXiv | 0 | 0 |
| visibility_off | Distilling Time Series Foundation Models for Efficient Forecasting | Yuqi Li, Kuiye Ding, Chuanguang Yang, Szu-Yu Chen, Yingli Tian | 2026-01-19 | ArXiv | 0 | 7 |
| visibility_off | Time-series forecasting for political violence targeting women | Myo Thida | 2025-12-09 | International Journal of Data Science and Analytics | 0 | 2 |
| Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |