Time-series forecasting
This page was last updated on 2026-02-16 06:33:24 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 | 373 | 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 | International Conference on Learning Representations, ArXiv | 150 | 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 | ArXiv, Neural Information Processing Systems | 49 | 54 | open_in_new |
| visibility_off | Sparse Graph Learning from Spatiotemporal Time Series | Andrea Cini, Daniele Zambon, C. Alippi | 2022-05-26 | Journal of machine learning research, J. Mach. Learn. Res. | 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 | 34 | 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 | ArXiv, Neural Information Processing Systems | 616 | 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 | 155 | 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 | DBLP, ArXiv | 496 | 16 | 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 | DBLP, ArXiv | 428 | 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 | International Conference on Learning Representations, ArXiv | 766 | 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 | ArXiv, Neural Information Processing Systems | 99 | 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 | ArXiv, Neural Information Processing Systems | 422 | 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 | 107 | 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 | 77 | 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 | 5 |
| visibility_off | Multi-view graph representing interactive learning network for time series forecasting | Guanshu Wang, Limin Liu, Bin Wu | 2026-01-18 | Journal of Big Data | 0 | 1 |
| 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 | Enhancing few-shot time series forecasting with LLM-guided diffusion | Haonan Shi, Dehua Shuai, Liming Wang, Xiyang Liu, Long Tian | 2026-01-19 | ArXiv | 0 | 2 |
| 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 | 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 | 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 | DiTS: Multimodal Diffusion Transformers Are Time Series Forecasters | Haoran Zhang, Haixuan Liu, Yong Liu, Yunzhong Qiu, Yuxuan Wang, Jianmin Wang, Mingsheng Long | 2026-02-06 | ArXiv | 0 | 33 |
| 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 | T-LLM: Teaching Large Language Models to Forecast Time Series via Temporal Distillation | Suhan Guo, Bingxu Wang, Shaodan Zhang, Furao Shen | 2026-02-02 | ArXiv | 0 | 0 |
| visibility_off | ASGMamba: Adaptive Spectral Gating Mamba for Multivariate Time Series Forecasting | Qianyang Li, Xingjun Zhang, Shaoxun Wang, Jia Wei, Yueqi Xing | 2026-02-02 | ArXiv | 0 | 7 |
| 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 | 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 | Empowering Time Series Analysis with Large-Scale Multimodal Pretraining | Peng Chen, Siyuan Wang, Shiyan Hu, Xingjian Wu, Yang Shu, Zhongwen Rao, Meng Wang, Yijie Li, Bin Yang, Chenjuan Guo | 2026-02-05 | ArXiv | 0 | 38 |
| visibility_off | LLM-driven hybrid architecture for multi-variate and multi-horizon forecasting of consumption patterns using graphs, recurrent units, and transformers | Ishpreet Kaur, Jatin Bedi, Ashutosh Aggarwal | 2026-01-31 | Discover Computing | 0 | 5 |
| visibility_off | Enhancing Multivariate Time Series Forecasting with Global Temporal Retrieval | Fanpu Cao, Lu Dai, Jindong Han, Hui Xiong | 2026-02-11 | ArXiv | 0 | 17 |
| visibility_off | CoGenCast: A Coupled Autoregressive-Flow Generative Framework for Time Series Forecasting | Yaguo Liu, Mingyue Cheng, Daoyu Wang, Xiaoyu Tao, Qi Liu | 2026-02-03 | ArXiv | 0 | 16 |
| visibility_off | Time-TK: A Multi-Offset Temporal Interaction Framework Combining Transformer and Kolmogorov-Arnold Networks for Time Series Forecasting | Fan Zhang, Shiming Fan, Hua Wang | 2026-01-30 | ArXiv | 0 | 11 |
| 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 | SEER: Transformer-based Robust Time Series Forecasting via Automated Patch Enhancement and Replacement | Xiangfei Qiu, Xvyuan Liu, Tianen Shen, Xingjian Wu, Hanyin Cheng, Bin Yang, Jilin Hu | 2026-01-31 | ArXiv | 0 | 22 |
| 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 | Bridging Time and Frequency: A Joint Modeling Framework for Irregular Multivariate Time Series Forecasting | Xiangfei Qiu, Kangjia Yan, Xvyuan Liu, Xingjian Wu, Jilin Hu | 2026-01-31 | ArXiv | 0 | 22 |
| visibility_off | DMamba: Decomposition-enhanced Mamba for Time Series Forecasting | Ruxuan Chen, Fang Sun | 2026-02-09 | ArXiv | 0 | 0 |
| 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 | 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 | 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 | 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 | 13 |
| 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 | Spatiotemporal decoupling-gated transformer: modeling high-dimensional coupling for traffic flow prediction | Gong Wang, Wei Sun, Junbo Gao, Chunyu Wang, Lai Wei | 2026-01-01 | Applied Intelligence | 0 | 7 |
| 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, P. Lio, Kwok-Yan Lam, S. Yiu | 2026-01-01 | ArXiv | 0 | 6 |
| visibility_off | Revisiting the Generic Transformer: Deconstructing a Strong Baseline for Time Series Foundation Models | Yunshi Wen, Wesley M. Gifford, Chandra Reddy, Lam M. Nguyen, Jayant Kalagnanam, A. A. Julius | 2026-02-06 | ArXiv | 0 | 8 |
| visibility_off | Learning from Historical Activations in Graph Neural Networks | Yaniv Galron, Hadar Sinai, Haggai Maron, Moshe Eliasof | 2026-01-03 | ArXiv | 0 | 11 |
| 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 | 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 | A Lightweight Multi-View Approach to Short-Term Load Forecasting | Julien Guit'e-Vinet, Alexandre Blondin Mass'e, 'Eric Beaudry | 2026-02-09 | ArXiv | 0 | 0 |
| 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 | 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 | 36 |
| 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 |
| Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |