Time-series forecasting
This page was last updated on 2026-03-30 06:48:08 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 | 409 | 55 | 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 | 158 | 58 | 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 | 52 | 55 | 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. | 30 | 55 | 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 | 37 | 55 | 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 | 662 | 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.org, ArXiv | 161 | 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 | 561 | 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 | 491 | 35 | 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 | 854 | 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 | 118 | 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 | 452 | 58 | 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 | 115 | 58 | open_in_new |
| visibility_off | AZ-whiteness test: a test for signal uncorrelation on spatio-temporal graphs | Daniele Zambon, C. Alippi | None | Neural Information Processing Systems, Advances in Neural Information Processing Systems 35 | 8 | 55 | open_in_new |
| visibility_off | Graph state-space models | Daniele Zambon, Andrea Cini, L. Livi, C. Alippi | 2023-01-04 | arXiv.org, ArXiv | 9 | 55 | 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 | Advances in Neural Information Processing Systems 37, Neural Information Processing Systems | 94 | 58 | 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 | TimeSqueeze: Dynamic Patching for Efficient Time Series Forecasting | S. Ankireddy, N. Seleznev, Nam H. Nguyen, Yulun Wu, Senthil Kumar, Furong Huang, C. B. Bruss | 2026-03-11 | ArXiv | 1 | 9 |
| visibility_off | Multi-scale hypergraph meets LLMs: Aligning large language models for time series analysis | Zongjiang Shang, Dongliang Cui, Binqing Wu, Ling Chen | 2026-02-04 | ArXiv | 3 | 7 |
| visibility_off | Deep TPC: Temporal-Prior Conditioning for Time Series Forecasting | Filippos Bellos, N. Premkumar, Yannis Avrithis, Nam H. Nguyen, Jason J. Corso | 2026-02-18 | ArXiv | 0 | 43 |
| visibility_off | MM-ISTS: Cooperating Irregularly Sampled Time Series Forecasting with Multimodal Vision-Text LLMs | Zhide Lei, Chenxi Liu, Hao Miao, Wanghui Qiu, Bin Yang, Chenjuan Guo | 2026-03-06 | ArXiv | 0 | 41 |
| visibility_off | IPatch: A Multi-Resolution Transformer Architecture for Robust Time-Series Forecasting | Ayman Harkati, Moncef Garouani, Olivier Teste, Julien Aligon, Mohamed Hamlich | 2026-03-25 | ArXiv | 0 | 9 |
| visibility_off | Timer-S1: A Billion-Scale Time Series Foundation Model with Serial Scaling | Yong Liu, Xin Su, Shiyu Wang, Haoran Zhang, Haixuan Liu, Yuxuan Wang, Zhou Ye, Yang Xiang, Jianmin Wang, Mingsheng Long | 2026-03-05 | ArXiv | 0 | 34 |
| visibility_off | Robust Long-Term Spatial–Temporal Forecasting for Dynamic Networks: The MDETST Model | Wenjing Feng, Lanhao Li, Huichao Zhou, Bingshu Xie, Dawei Zhao, Yi Zhang, Feifei Wang | 2026-02-13 | Mathematics | 0 | 5 |
| 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 | 1 | 34 |
| visibility_off | T-LLM: Teaching Large Language Models to Forecast Time Series via Temporal Distillation | Suhan Guo, Bingxu Wang, Shaodan Zhang, Shen Furao | 2026-02-02 | ArXiv | 0 | 8 |
| visibility_off | Reverso: Efficient Time Series Foundation Models for Zero-shot Forecasting | Xing Fu, Yanhong Li, Georgios Papaioannou, Yoon Kim | 2026-02-19 | ArXiv | 0 | 4 |
| 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 | 8 |
| visibility_off | EnTransformer: A Deep Generative Transformer for Multivariate Probabilistic Forecasting | Rajdeep Pathak, R. Goswami, Madhurima Panja, P. Ghosh, Tanujit Chakraborty | 2026-03-12 | ArXiv | 0 | 9 |
| visibility_off | MantisV2: Closing the Zero-Shot Gap in Time Series Classification with Synthetic Data and Test-Time Strategies | Vasilii Feofanov, Songkang Wen, Jianfeng Zhang, Lujia Pan, I. Redko | 2026-02-19 | ArXiv | 0 | 16 |
| visibility_off | TiMi: Empower Time Series Transformers with Multimodal Mixture of Experts | Jiafeng Lin, Yuxuan Wang, Huakun Luo, Zhongyi Pei, Jianmin Wang | 2026-02-25 | ArXiv | 0 | 9 |
| visibility_off | Deep Autocorrelation Modeling for Time-Series Forecasting: Progress and Prospects | Hao Wang, Licheng Pan, Qingsong Wen, Jialin Yu, Zhichao Chen, Chunyuan Zheng, Xiaoxi Li, Zhixuan Chu, Chao Xu, Mingming Gong, Haoxuan Li, Yuan Lu, Zhouchen Lin, Philip Torr, Yan Liu | 2026-03-20 | ArXiv | 0 | 14 |
| 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 | 41 |
| visibility_off | DualWeaver: Synergistic Feature Weaving Surrogates for Multivariate Forecasting with Univariate Time Series Foundation Models | Jinpeng Li, Zhongyi Pei, Huaze Xue, Bojian Zheng, Chen Wang, Jianmin Wang | 2026-02-25 | ArXiv | 0 | 9 |
| visibility_off | Enhancing Multivariate Time Series Forecasting with Global Temporal Retrieval | Fanpu Cao, Lu Dai, Jindong Han, Hui Xiong | 2026-02-11 | ArXiv | 1 | 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 | 19 |
| 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 | Preference Guided Meta-Learning for Cross Domain Time Series Forecasting | Xingwang Li, Fei Teng, Tianrui Li, Qiang Duan | 2026-04-01 | IEEE Transactions on Knowledge and Data Engineering | 0 | 12 |
| visibility_off | Baguan-TS: A Sequence-Native In-Context Learning Model for Time Series Forecasting with Covariates | Linxiao Yang, Xuejia Jiang, Gezheng Xu, Tian Zhou, Min Yang, Zhaoyang Zhu, Linyuan Geng, Zhipeng Zeng, Qiming Chen, Xinyue Gu, Rong Jin, Liang Sun | 2026-03-18 | ArXiv | 0 | 11 |
| visibility_off | SEER: Transformer-based Robust Time Series Forecasting via Automated Patch Enhancement and Replacement | Xiangfei Qiu, Xvyuan Liu, Tian Shen, Xingjian Wu, Hanyin Cheng, Bin Yang, Jilin Hu | 2026-01-31 | ArXiv | 0 | 23 |
| 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 | 23 |
| visibility_off | Learning Recursive Multi-Scale Representations for Irregular Multivariate Time Series Forecasting | Boyuan Li, Zhen Liu, Yicheng Luo, Qianli Ma | 2026-02-25 | ArXiv | 0 | 7 |
| visibility_off | DMamba: Decomposition-enhanced Mamba for Time Series Forecasting | Ruxuan Chen, Fang Sun | 2026-02-09 | ArXiv | 0 | 2 |
| visibility_off | Forecasting with Guidance: Representation-Level Supervision for Time Series Forecasting | Jiacheng Wang, Liang Fan, Baihua Li, Luyang Zhang | 2026-03-25 | ArXiv | 0 | 2 |
| visibility_off | Spectral Text Fusion: A Frequency-Aware Approach to Multimodal Time-Series Forecasting | Huu Hiep Nguyen, Minh Hoang Nguyen, Dung Nguyen, Hung Le | 2026-02-02 | ArXiv | 0 | 3 |
| visibility_off | EIDOS: Latent-Space Predictive Learning for Time Series Foundation Models | Xinxing Zhou, Qingren Yao, Yiji Zhao, Chenghao Liu, Flora D. Salim, Xiaojie Yuan, Yan Wen, Ming Jin | 2026-02-15 | ArXiv | 0 | 4 |
| visibility_off | Revisiting the Generic Transformer: Deconstructing a Strong Baseline for Time Series Foundation Models | Yu-Wei Wen, Wesley M. Gifford, Chandra Reddy, Lam M. Nguyen, Jayant Kalagnanam, A. A. Julius | 2026-02-06 | ArXiv | 1 | 8 |
| visibility_off | STEP: Scientific Time-Series Encoder Pretraining via Cross-Domain Distillation | Chen Zhang, Liwei Liu, Jun Tao, Xiaoyu Yang, Xuenan Xu, Kai Chen, Bowen Zhou, Wen Wu, Chao Zhang | 2026-03-19 | ArXiv | 0 | 7 |
| visibility_off | Memory-Augmented Spatio-Temporal Transformer for Robust Traffic Flow Forecasting | Puqing Hu, Chunjiang Wu, Chen Wang, Xin Yang, Zhibin Li, Tinghui Chen, Shijie Zhou | 2026-03-01 | Biomimetics | 0 | 4 |
| visibility_off | Collaborative Multivariate Time Series Forecasting via Variable-Tailored Inter-temporal Graph and Adaptive-Smooth Frequency Fusion | Jierui Lei, Peng Peng, Haina Tang, Xudong Zhang, Fangzheng Chen, Wenjian Zhang | 2026-03-01 | Machine Learning | 0 | 4 |
| visibility_off | GraFT: Infusing Pre-trained Transformers with Relational Structure for Time Series Forecasting | Yuqi Yuan, Xiong Luo, Qiaojuan Peng, Wenbing Zhao | 2026-03-14 | DBLP | 0 | 9 |
| visibility_off | Rethinking the Role of LLMs in Time Series Forecasting | Xin Qiu, Junlong Tong, Yirong Sun, Yunpu Ma, Wei Zhang, Xiaoyu Shen | 2026-02-16 | ArXiv | 2 | 6 |
| visibility_off | Adapt Data to Model: Adaptive Transformation Optimization for Domain-shared Time Series Foundation Models | Yunzhong Qiu, Zhiyao Cen, Zhongyi Pei, Chen Wang, Jianmin Wang | 2026-02-28 | ArXiv | 0 | 9 |
| visibility_off | Be Wary of Your Time Series Preprocessing | Sofiane Ennadir, Tianze Wang, Oleg Smirnov, Sahar Asadi, Lele Cao | 2026-02-19 | ArXiv | 0 | 5 |
| visibility_off | A Lightweight Multi-View Approach to Short-Term Load Forecasting | Julien Guit'e-Vinet, Alexandre Blondin Mass'e, Éric Beaudry | 2026-02-09 | ArXiv | 0 | 1 |
| visibility_off | How Effective Is Mamba-Augmented Transformer for Stock Market Price Forecasting? | Md. Shahria Sarker Shuvo, Awsaf Tausif Adib, Md. Estehaar Ahmed Emon, A. Rafi, Rashedur M. Rahman | 2026-02-09 | FinTech | 0 | 9 |
| visibility_off | An Optimization Method for Autoregressive Time Series Forecasting | Zheng Li, Jerry Q. Cheng, Huanying Gu | 2026-02-02 | ArXiv | 0 | 2 |
| visibility_off | Quantum-enhanced architectures for multivariate time-series forecasting | S. Ranilla-Cortina, D. A. Aranda, J. Ballesteros, J. Bonilla, N. Monrio, E. Combarro | 2026-02-01 | The Journal of Supercomputing | 0 | 20 |
| visibility_off | PHAT: Modeling Period Heterogeneity for Multivariate Time Series Forecasting | Jiaming Ma, Qihe Huang, Hao Ma, Guanjun Wang, Sheng Huang, Zhen-Qiang Zhou, Pengkun Wang, Binwu Wang, Yang Wang | 2026-01-31 | ArXiv | 2 | 14 |
| visibility_off | TS-MLLM: A Multi-Modal Large Language Model-based Framework for Industrial Time-Series Big Data Analysis | Haiteng Wang, Yikang Li, Yunfei Zhu, Jing Yan, Lei Ren, Laurence T. Yang | 2026-03-08 | ArXiv | 0 | 6 |
| visibility_off | From Empirical Analysis to Mixture‐of‐Experts Modeling: Zero‐Shot Cross‐Frequency Forecasting in Real‐Time Photovoltaic Management | Issei Suemitsu, T. Kono, Ryo Wakabayashi, J. Tsunoda, Yosuke Yamaguchi, Wenpeng Wei | 2026-02-01 | Advanced Energy and Sustainability Research | 0 | 5 |
| visibility_off | PaAno: Patch-Based Representation Learning for Time-Series Anomaly Detection | Jinju Park, Seokho Kang | 2026-02-01 | ArXiv | 0 | 1 |
| Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |