Time-series forecasting
This page was last updated on 2025-12-15 06:14:13 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 | 300 | 53 | 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 | 141 | 56 | 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 | 45 | 53 | 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 | 53 | 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 | 26 | 53 | 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 | 552 | 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 | 132 | 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 | 423 | 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 | 376 | 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 | International Conference on Learning Representations, ArXiv | 662 | 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 | 82 | 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 | 391 | 56 | 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 | 98 | 56 | open_in_new |
| visibility_off | AZ-whiteness test: a test for signal uncorrelation on spatio-temporal graphs | Daniele Zambon, C. Alippi | None | DBLP | 8 | 53 | open_in_new |
| visibility_off | Graph state-space models | Daniele Zambon, Andrea Cini, L. Livi, C. Alippi | 2023-01-04 | arXiv.org, ArXiv | 8 | 53 | 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 | 57 | 56 | 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 | 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 | Xihe: Scalable Zero-Shot Time Series Learner Via Hierarchical Interleaved Block Attention | Yinbo Sun, Yuchen Fang, Zhibo Zhu, Jia Li, Yu Liu, Qiwen Deng, Jun Zhou, Hang Yu, Xingyu Lu, Lintao Ma | 2025-10-20 | ArXiv | 0 | 6 |
| visibility_off | InvDec: Inverted Decoder for Multivariate Time Series Forecasting with Separated Temporal and Variate Modeling | Yuhang Wang | 2025-10-23 | ArXiv | 0 | 0 |
| visibility_off | Chronos-2: From Univariate to Universal Forecasting | Abdul Fatir Ansari, Oleksandr Shchur, Jaris Kuken, Andreas Auer, Boran Han, Pedro Mercado, Syama Sundar Rangapuram, Huibin Shen, Lorenzo Stella, Xiyuan Zhang, Mononito Goswami, Shubham Kapoor, Danielle C. Maddix, Pablo Guerron, Tony Hu, Junming Yin, Nick Erickson, Prateek Mutalik Desai, Hao Wang, H. Rangwala, G. Karypis, Yuyang Wang, Michael Bohlke-Schneider | 2025-10-17 | ArXiv | 6 | 38 |
| 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 | MAP4TS: A Multi-Aspect Prompting Framework for Time-Series Forecasting with Large Language Models | Suchan Lee, Jihoon Choi, Sohyeon Lee, Minseok Song, Bong-Gyu Jang, Hwanjo Yu, S. Han | 2025-10-27 | ArXiv | 0 | 21 |
| 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 | 0 |
| visibility_off | HN-MVTS: HyperNetwork-based Multivariate Time Series Forecasting | Andrey Savchenko, Oleg Kachan | 2025-11-11 | ArXiv | 0 | 1 |
| visibility_off | Fighter: Unveiling the Graph Convolutional Nature of Transformers in Time Series Modeling | Chen Zhang, Weixin Bu, Wendong Xu, Runsheng Yu, Yik-Chung Wu, Ngai Wong | 2025-10-20 | ArXiv | 0 | 2 |
| 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 | 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 | SwiftTS: A Swift Selection Framework for Time Series Pre-trained Models via Multi-task Meta-Learning | Tengxue Zhang, Biao Ouyang, Yang Shu, Xinyang Chen, Chenjuan Guo, Bin Yang | 2025-10-27 | ArXiv | 0 | 37 |
| visibility_off | Hydra: Dual Exponentiated Memory for Multivariate Time Series Analysis | Asal Meskin, Alireza Mirrokni, Ali Najar, Ali Behrouz | 2025-11-02 | ArXiv | 0 | 0 |
| 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 | MGTS-Net: Exploring Graph-Enhanced Multimodal Fusion for Augmented Time Series Forecasting | Shule Hao, Junpeng Bao, Wenli Li | 2025-10-18 | ArXiv | 0 | 1 |
| visibility_off | DualMamba: a patch-based model with dual mamba for long-term time series forecasting | Guang-Yu Wei, Hui-Chuan Huang, Zhi-Qing Zhong, Wen-Long Sun, Yong-Hao Wan, Ai-Min Feng | 2025-10-21 | Frontiers of Computer Science | 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 | 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 | SEMPO: Lightweight Foundation Models for Time Series Forecasting | Hui He, Kun Yi, Yuanchi Ma, Qi Zhang, Zhendong Niu, Guansong Pang | 2025-10-22 | ArXiv | 0 | 9 |
| 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 | 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 | MSTN: Fast and Efficient Multivariate Time Series Model | Sumit Shevtekar, Chandresh Kumar Maurya, Gourab Sil | 2025-11-25 | ArXiv | 0 | 7 |
| visibility_off | Position-Invariant Graph Convolutional Recurrent Network for Traffic Forecasting | Xiao Liu, Shaohua Li, Weimin Li, Xiao Yu, Jingchao Wang, A. M. Luvembe, Quan-Ke Pan, Fangfang Liu | 2025-12-01 | IEEE Transactions on Intelligent Transportation Systems | 0 | 14 |
| visibility_off | Pre-trained Forecasting Models: Strong Zero-Shot Feature Extractors for Time Series Classification | Andreas Auer, Daniel Klotz, Sebastinan Bock, Sepp Hochreiter | 2025-10-30 | ArXiv | 1 | 58 |
| visibility_off | Adaptive Normalization Mamba with Multi Scale Trend Decomposition and Patch MoE Encoding | MinCheol Jeon | 2025-12-07 | ArXiv | 0 | 0 |
| visibility_off | Forecast2Anomaly (F2A): Adapting Multivariate Time Series Foundation Models for Anomaly Prediction | Atif Hassan, Tarun Kumar, Ashish Mishra, S. Serebryakov, Satish Kumar Mopur, Phanidhar Koganti, Murthy Chelankuri, Ramanagopal V. Vogety, Suparna Bhattacharya, Martin Foltin | 2025-11-05 | ArXiv | 0 | 4 |
| 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 | OneCast: Structured Decomposition and Modular Generation for Cross-Domain Time Series Forecasting | Tingyue Pan, Mingyue Cheng, Shilong Zhang, Zhiding Liu, Xiaoyu Tao, Yucong Luo, Jintao Zhang, Qi Liu | 2025-10-28 | ArXiv | 0 | 9 |
| 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 | Evaluating Large Language Models for Turboshaft Engine Torque Prediction | Alessandro Tronconi, David He, Eric Bechhoefer | 2025-10-26 | Annual Conference of the PHM Society | 0 | 1 |
| 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 | 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 | 0 | 9 |
| 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 | 0 | 6 |
| visibility_off | Attentional Bi-LSTM for Multivariate Time Series Forecasting on Edge Devices: A Case Study on NanoPi Neo Plus2 | Navid Hajizadeh, Saeed Yazdani, Sara Ershadi-Nasab | 2025-10-28 | 2025 15th International Conference on Computer and Knowledge Engineering (ICCKE) | 0 | 3 |
| visibility_off | IBMA: An Imputation-Based Mixup Augmentation Using Self-Supervised Learning for Time Series Data | Dang Nha Nguyen, Hai Dang Nguyen, Khoa Tho Anh Nguyen | 2025-11-11 | ArXiv | 0 | 0 |
| Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |