Time-series forecasting
This page was last updated on 2026-01-05 06:15:49 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 | 323 | 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 | 142 | 57 | 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 | 47 | 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 | 28 | 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 | 28 | 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 | 565 | 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 | 138 | 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 | 434 | 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 | 384 | 33 | 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 | 683 | 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 | 85 | 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 | 402 | 57 | 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 | ArXiv, DBLP | 99 | 57 | 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.org, ArXiv | 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 | 58 | 57 | 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 | STELLA: Guiding Large Language Models for Time Series Forecasting with Semantic Abstractions | Junjie Fan, Hongye Zhao, Linduo Wei, Jiayu Rao, Guijia Li, Jiaxin Yuan, Wenqi Xu, Yong Qi | 2025-12-04 | ArXiv | 0 | 1 |
| visibility_off | FiCoTS: Fine-to-Coarse LLM-Enhanced Hierarchical Cross-Modality Interaction for Time Series Forecasting | Ya-Nan Lyu, Hao Zhou, Lu Zhang, Xu Yang, Zhiyong Liu | 2025-11-29 | ArXiv | 0 | 12 |
| visibility_off | Tiny-TSM: Efficiently Training a Lightweight SOTA Time Series Foundation Model | Felix Birkel | 2025-11-24 | ArXiv | 0 | 1 |
| 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 | BiSTAG-TS: a dual-stream generative framework for symbolic–numerical time series forecasting via large language models | Ruidi Yang, Yuxing Mao, Hengyu Yan, Zijie Wei, Jian Li, Jianyu Pan | 2025-12-01 | The Journal of Supercomputing | 0 | 3 |
| 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 | HN-MVTS: HyperNetwork-based Multivariate Time Series Forecasting | Andrey Savchenko, Oleg Kachan | 2025-11-11 | ArXiv | 0 | 1 |
| visibility_off | Quantum-enhanced dual-layer graph attention network for time-series forecasting | Yongli Tang, Zhongqi Cai, Yue Zhang, Zhenlun Gao, Jinxia Yu | 2025-11-14 | Scientific Reports | 1 | 1 |
| visibility_off | MSTN: Fast and Efficient Multivariate Time Series Prediction Model | Sumit S Shevtekar, Chandresh Kumar Maurya, Gourab Sil | 2025-11-25 | ArXiv | 0 | 7 |
| visibility_off | AdaPatch: Adaptive Patch-Level Modeling for Non-Stationary Time Series Forecasting | Kun Liu, Zhongjie Duan, Cen Chen, Yanhao Wang, Dawei Cheng, Yuqi Liang | 2025-11-10 | Proceedings of the 34th ACM International Conference on Information and Knowledge Management | 0 | 8 |
| 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 | Seeing Sequences like Humans: Pattern Classification Driven Time-Series Forecasting via Vision Language Models | Xingyu Liu, Min Gao, Zongwei Wang, Yinbing Bai | 2025-11-10 | Proceedings of the 34th ACM International Conference on Information and Knowledge Management | 0 | 9 |
| visibility_off | A Causal-Guided Multimodal Large Language Model for Generalized Power System Time-Series Data Analytics | Zhenghao Zhou, Yiyan Li, Xinjie Yu, Runlong Liu, Zelin Guo, Zheng Yan, Mo-Yuen Chow, Yuqi Yang, Yang Xu | 2025-11-11 | ArXiv | 0 | 2 |
| visibility_off | EAPformer: Entropy-Aware Patch Transformer for Multivariate Long-Term Time Series Forecasting | Jiahao Ling, Xuan Yang, Shiming Gong, Bo Gu | 2025-11-10 | Proceedings of the 34th ACM International Conference on Information and Knowledge Management | 0 | 11 |
| visibility_off | EMAformer: Enhancing Transformer through Embedding Armor for Time Series Forecasting | Zhiwei Zhang, Xinyi Du, Xuanchi Guo, Weihao Wang, Wenjuan Han | 2025-11-11 | ArXiv | 0 | 2 |
| 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 | 30 |
| visibility_off | TimeSense:Making Large Language Models Proficient in Time-Series Analysis | Zhirui Zhang, Changhua Pei, Tianyi Gao, Zhe Xie, Yibo Hao, Zhaoyang Yu, Longlong Xu, Tong Xiao, Jing Han, Dan Pei | 2025-11-09 | ArXiv | 0 | 11 |
| visibility_off | Time Series Forecasting via Direct Per-Step Probability Distribution Modeling | Linghao Kong, Xiaopeng Hong | 2025-11-28 | ArXiv | 0 | 0 |
| visibility_off | Moirai 2.0: When Less Is More for Time Series Forecasting | Chenghao Liu, Taha İbrahim Aksu, Juncheng Liu, Xu Liu, Hanshu Yan, Quang Pham, Doyen Sahoo, Caiming Xiong, Silvio Savarese, Junnan Li | 2025-11-12 | ArXiv | 1 | 33 |
| 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 | PeriodNet: Boosting the Potential of Attention Mechanism for Time Series Forecasting | Bowen Zhao, Huanlai Xing, Zhiwen Xiao, Jincheng Peng, Li Feng, Xinhan Wang, Rong Qu, Hui Li | 2025-11-23 | ArXiv | 0 | 19 |
| 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 | The Few Govern the Many:Unveiling Few-Layer Dominance for Time Series Models | Xin Qiu, Junlong Tong, Yirong Sun, Yunpu Ma, Xiaoyu Shen | 2025-11-10 | ArXiv | 0 | 4 |
| visibility_off | Neural Network Approaches to Temporal Pattern Recognition: Applications in Demand Forecasting and Predictive Analytics | Ying Wang, Shi Qiu, Zifan Chen | 2025-11-11 | Journal of Banking and Financial Dynamics | 0 | 0 |
| visibility_off | APT: Affine Prototype-Timestamp For Time Series Forecasting Under Distribution Shift | Yujie Li, Zezhi Shao, Chengqing Yu, Yisong Fu, Tao Sun, Yongjun Xu, Fei Wang | 2025-11-17 | ArXiv | 0 | 13 |
| visibility_off | Adaptive Normalization Mamba with Multi Scale Trend Decomposition and Patch MoE Encoding | MinCheol Jeon | 2025-12-07 | ArXiv | 0 | 0 |
| visibility_off | GPT-2-Augmented Sequence Modeling for Short-Term Load Forecasting | Kun Xu, Ying Wang, Shuomin Wu, Wenjing Zhang, Jingxiao Jingxiao, Jiang, Kaifeng Zhang | 2025-11-07 | 2025 IEEE China International Youth Conference on Electrical Engineering (CIYCEE) | 0 | 13 |
| visibility_off | LiteMixer: Scalable, Low-Overhead Multi-Scale Mixing for Time Series Forecasting | Issam Ait Yahia, Abdelkader El Mahdaouy, Soufiane Oualil, Ismail Berrada | 2025-11-25 | 2025 12th International Conference on Wireless Networks and Mobile Communications (WINCOM) | 0 | 3 |
| visibility_off | TS2Vec-Ensemble: An Enhanced Self-Supervised Framework for Time Series Forecasting | Ganeshan Niroshan, Uthayasanker Thayasivam | 2025-11-27 | ArXiv | 0 | 12 |
| visibility_off | Zero-shot forecasting of optical network telemetry using large language models | K. Abdelli | 2025-11-12 | Journal of Optical Communications and Networking | 0 | 9 |
| visibility_off | Are Time-Indexed Foundation Models the Future of Time Series Imputation? | E. L. Naour, Tahar Nabil, Adrien Petralia, G. Agoua | 2025-11-08 | ArXiv | 0 | 4 |
| 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 | MSOFormer: Multi-scale Transformer with Orthogonal Embedding and Frequency Modeling for Multivariate Time Series Forecasting | Qin Shi, Chu Xu, Zongtang Hu, Dong Shen, Dapeng Sun, Lijun Quan | 2025-11-10 | Proceedings of the 34th ACM International Conference on Information and Knowledge Management | 0 | 11 |
| visibility_off | Structured Noise Modeling for Enhanced Time-Series Forecasting | Sepideh Koohfar | 2025-11-24 | ArXiv | 0 | 2 |
| visibility_off | MAC2STI: Mamba network with autoregressive clustering for two-stage spatio-temporal imputation | Jinyu Fan, Jun Ma, Hongtao Gai | 2025-11-25 | Complex & Intelligent Systems | 0 | 0 |
| visibility_off | Extracting Global Temporal Patterns Within Short Look-Back Windows for Traffic Forecasting | Bo Sun, Zhe Wu, Zhiyuan Deng, Li Su, Qingfang Zheng | 2025-11-10 | Proceedings of the 34th ACM International Conference on Information and Knowledge Management | 0 | 2 |
| visibility_off | Bidirectional Temporal-Aware Modeling with Multi-Scale Mixture-of-Experts for Multivariate Time Series Forecasting | Yifan Gao, Boming Zhao, Haocheng Peng, Hujun Bao, Jiashu Zhao, Zhaopeng Cui | 2025-11-10 | Proceedings of the 34th ACM International Conference on Information and Knowledge Management | 1 | 9 |
| visibility_off | HRCformer: Hierarchical Recursive Convolution-Transformer with Multi-Scale Adaptive Recalibration for Time Series Forecasting | Dejiang Zhang, Lianyong Qi, Yuwen Liu, Xucheng Zhou, Jianye Xie, Haolong Xiang, Xiaolong Xu, Xuyun Zhang, Yang Cao, Yang Zhang | 2025-11-10 | Proceedings of the 34th ACM International Conference on Information and Knowledge Management | 0 | 14 |
| visibility_off | Weaver: Kronecker Product Approximations of Spatiotemporal Attention for Traffic Network Forecasting | Christopher Cheong, Gary Davis, Seongjin Choi | 2025-11-12 | ArXiv | 0 | 1 |
| visibility_off | CometNet: Contextual Motif-guided Long-term Time Series Forecasting | Weixu Wang, Xiaobo Zhou, Xin Qiao, Lei Wang, Tie Qiu | 2025-11-11 | ArXiv | 0 | 5 |
| visibility_off | COLLAR: combating low-rank temporal latent representation for high-dimensional multivariate time series prediction using dynamic Koopman regularization | Qifa Peng, Simin An, Siyu Nie, Yong Su | 2025-11-21 | Journal of Big Data | 1 | 6 |
| visibility_off | IBMA: An Imputation-Based Mixup Augmentation Using Self-Supervised Learning for Time Series Data | Dang Nha Nguyen, Hai Dang Nguyen, K. N. A. Nguyen | 2025-11-11 | ArXiv | 0 | 0 |
| Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |