Time-series forecasting
This page was last updated on 2026-05-11 07:27:01 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 | 437 | 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 | ArXiv, International Conference on Learning Representations | 168 | 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 | 54 | 55 | 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 | 32 | 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 | 42 | 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 | ArXiv, Neural Information Processing Systems | 694 | 19 | 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 | 166 | 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 | 604 | 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 | 517 | 36 | 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 | 915 | 15 | 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 | 128 | 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 | 472 | 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 | 121 | 59 | 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 | 9 | 55 | open_in_new |
| visibility_off | Graph State-Space Models and Latent Relational Inference | Daniele Zambon, Andrea Cini, L. Livi, C. Alippi | 2023-01-04 | 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 | 101 | 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 | STELA: Spatiotemporal Forecasting via Graph Learning and Entropy-Guided LLM Adaptation | Tiantian Huang, Yue Li, Wei Shao, Ziqi Xu, Qipeng Song, Hui Li | 2026-04-13 | Proceedings of the ACM Web Conference 2026 | 0 | 4 |
| visibility_off | TimeSAF: Towards LLM-Guided Semantic Asynchronous Fusion for Time Series Forecasting | Fan Zhang, Shiming Fan, Hua Wang | 2026-04-14 | ArXiv | 0 | 11 |
| visibility_off | Irregularly Sampled Time Series Classification via Fusing Language Models and Multi‐Channel Image Representations | Zichen Li, Faming Lu, Zedong Lin, Qingtian Zeng, Yunxia Bao | 2026-03-24 | Concurrency and Computation: Practice and Experience | 0 | 7 |
| visibility_off | TempusBench: An Evaluation Framework for Time-Series Forecasting | Denizalp Goktas, G. Riaño-Briceño, A. Abdullah, Aryan Nair, Chenkai Shen, Beatriz de Lucio, Alexandra Magnusson, Farhan Mashrur, A. Abdulla, Shawrna Sen, Mahitha Thippireddy, G. Schwartz, Amy Greenwald | 2026-04-13 | ArXiv | 1 | 7 |
| 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 | MICA: Multivariate Infini Compressive Attention for Time Series Forecasting | Willa Potosnak, Nina Zukowska, Michał Wiliński, D. Howarth, Ignacy Stkepka, Mononito Goswami, Artur W. Dubrawski | 2026-04-07 | ArXiv | 0 | 12 |
| visibility_off | Routing Channel-Patch Dependencies in Time Series Forecasting with Graph Spectral Decomposition | Dongyuan Li, Shun Zheng, Chang Xu, Jiang Bian, Renhe Jiang | 2026-03-14 | ArXiv | 0 | 9 |
| visibility_off | A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks | Anish Saha, K. Shmakov | 2026-03-23 | ArXiv | 0 | 21 |
| 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 | A Roadmap for Parameter Selection of TFT and PatchTST Machine Learning Models | Saša Milić, Živko Sokolović, Luka Ivanović, Filip Zec | 2026-03-18 | 2026 25th International Symposium INFOTEH-JAHORINA (INFOTEH) | 0 | 2 |
| 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 | A Large Language Model for Traffic Flow Prediction Based on Stationary Wavelet Transform and Graph Convolutional Networks | Xin Wang, Gang Liu, Jing He, X. Zhou, Zhiyong Luo | 2026-04-11 | ISPRS International Journal of Geo-Information | 0 | 9 |
| visibility_off | WaveMoE: A Wavelet-Enhanced Mixture-of-Experts Foundation Model for Time Series Forecasting | Shunyu Wu, Jiawei Huang, Weibing Feng, Boxing Li, Xiao Zhang, Erli Meng, Dan Li, Jian Lou, See-Kiong Ng | 2026-04-12 | ArXiv | 0 | 7 |
| visibility_off | FAST: A Synergistic Framework of Attention and State-space Models for Spatiotemporal Traffic Prediction | Xinjin Li, Jinghan Cao, Mengyue Wang, Yue Wu, Long Yan, Yeyang Zhou, Ziqi Sha, Yu Ma | 2026-04-15 | ArXiv | 1 | 7 |
| 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 | A Family of Open Time-Series Foundation Models for the Radio Access Network | Ioannis Panitsas, L. Tassiulas | 2026-04-05 | ArXiv | 0 | 15 |
| visibility_off | ITS-Mina: A Harris Hawks Optimization-Based All-MLP Framework with Iterative Refinement and External Attention for Multivariate Time Series Forecasting | Pourya Zamanvaziri, Amirhossein Sadr, Aida Pakniyat, D. Rahmati | 2026-04-30 | ArXiv | 0 | 5 |
| visibility_off | Cross-RAG: Zero-Shot Retrieval-Augmented Time Series Forecasting via Cross-Attention | Seunghan Lee, Jaehoon Lee, Junyoung Seo, Sungdong Yoo, Minjae Kim, Taeheon Lim, Dongwan Kang, Hwanil Choi, Soonyoung Lee, Wonbin Ahn | 2026-03-16 | ArXiv | 0 | 10 |
| 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 | 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 | AdaMamba: Adaptive Frequency-Gated Mamba for Long-Term Time Series Forecasting | Xudong Jiang, Min Loo, Hanchen Yang, Wengen Li, Mingrui Zhang, Yichao Zhang, Jihong Guan, Shuigeng Zhou | 2026-04-25 | ArXiv | 0 | 16 |
| visibility_off | Automated Model Selection for Multivariate Time Series Forecasting | Xiaoxuan Fan, Jiaqi Sun, Xianjun Deng, Qiankun Zhang, Wei Xiang, Shenghao Liu, Lingzhi Yi | 2026-04-12 | Proceedings of the ACM Web Conference 2026 | 0 | 17 |
| visibility_off | TriTS: Time Series Forecasting from a Multimodal Perspective | Xiang Ao | 2026-04-17 | ArXiv | 0 | 1 |
| visibility_off | Meteorology-Driven GPT4AP: A Multi-Task Forecasting LLM for Atmospheric Air Pollution in Data-Scarce Settings | Prasanjit Dey, Soumyabrata Dev, Bianca Schoen-Phelan | 2026-03-31 | ArXiv | 0 | 9 |
| visibility_off | Traffic Flow Prediction on the Spatial Graph Convolutional Networks and Temporal Transformer Model | Kaize Xu | 2026-03-15 | Mathematical Modeling and Algorithm Application | 0 | 0 |
| visibility_off | DecompKAN: Decomposed Patch-KAN for Long-Term Time Series Forecasting | N. Mysore | 2026-04-27 | ArXiv | 1 | 8 |
| visibility_off | Zero-shot forecasting of streamflow using time series foundation models: are we there yet? | Alexander Y. Sun, Albert A Sun | 2026-03-20 | Machine Learning: Earth | 0 | 5 |
| visibility_off | ODGNet: Learning Dynamic Variable Association for Online Time Series Forecasting | Yushuo Liu, Yulong Wang, Kai Wang | 2026-06-01 | IEEE Transactions on Knowledge and Data Engineering | 0 | 6 |
| visibility_off | Foundation Models for Time Series Forecasting: Evidence from the Fuel Sector | Jonas Krause, Alex C. D. Lopes, Lucas G. M. Castro, André G. R. Ribeiro, M. A. Mochinski, E. Paraiso, Fabrício Enembreck, J. P. Barddal, Alceu de Souza Britto Jr, V. M. A. Souza | 2026-05-04 | Journal of the Brazilian Computer Society | 0 | 19 |
| visibility_off | FreAPNet: Learnable Amplitude–Phase Parameterization and Dual‐Path Frequency Learning for Multivariate Time Series Forecasting | Nannan Xu, Kecheng Xu, Yuanyuan Cui, GuoHai Yang, Meng Huang | 2026-03-31 | Concurrency and Computation: Practice and Experience | 0 | 6 |
| visibility_off | Temporal Patch Shuffle (TPS): Leveraging Patch-Level Shuffling to Boost Generalization and Robustness in Time Series Forecasting | Jafar Bakhshaliyev, Johannes Burchert, Niels Landwehr, Lars Schmidt-Thieme | 2026-04-10 | ArXiv | 0 | 5 |
| visibility_off | Superposition Is Not Necessary: A Mechanistic Interpretability Analysis of Transformer Representations for Time Series Forecasting | A. Yildirim | 2026-05-06 | ArXiv | 0 | 0 |
| visibility_off | ADAPTive Input Training for Many-to-One Pre-Training on Time-Series Classification | P. Quinlan, Qingguo Li, Xiaodan Zhu | 2026-04-09 | ArXiv | 0 | 5 |
| visibility_off | TC-KAN: Time-Conditioned Kolmogorov–Arnold Networks with Time-Dependent Activations for Long-Term Time Series Forecasting | Ziyu Shen, Yifan Fu, Liguo Weng, Keji Han, Yiqing Xu | 2026-04-01 | Sensors (Basel, Switzerland) | 0 | 9 |
| visibility_off | Accurate and Efficient Multi-Channel Time Series Forecasting via Sparse Attention Mechanism | Lei Gao, He Bao, Jin Fang, Guangzhen Wu, Weihua Zhou, Yun Zhou | 2026-03-19 | ArXiv | 0 | 3 |
| visibility_off | Seeking SOTA: Time-Series Forecasting Must Adopt Taxonomy-Specific Evaluation to Dispel Illusory Gains | Raeid Saqur, Christoph Bergmeir, Blanka Horvath, Daniel F. Schmidt, Frank Rudzicz, Terry Lyons | 2026-03-16 | ArXiv | 0 | 5 |
| visibility_off | CombinationTS: A Modular Framework for Understanding Time-Series Forecasting Models | Xiaoru Wang, Fanda Fan, Chenxi Wang, Yuxuan Yang, Rui Tang, Kuoyu Gao, Simiao Pang, Yuanfeng Shang, Zhipeng Liu, Wanling Gao, Lei Wang, Jianfeng Zhan | 2026-05-02 | ArXiv | 0 | 16 |
| visibility_off | Multimodal Forecasting for Commodity Prices Using Spectrogram-Based and Time Series Representations | Soyeon Park, Doohee Chung, Charmgil Hong | 2026-03-28 | ArXiv | 0 | 2 |
| visibility_off | Shift-Resilient Diffusive Imputation for Variable Subset Forecasting | Haihua Xu, Qi Hao, He Zhang, Jianpeng Zhao, Ziyue Qiao, Lu Jiang, Pengfei Wang, Yingjie Zhou, Pengyang Wang | 2026-04-12 | Proceedings of the ACM Web Conference 2026 | 0 | 8 |
| visibility_off | Text Summarization With Graph Attention Networks | M. Ardestani, Yllias Chali | 2026-04-04 | DBLP, ArXiv | 0 | 20 |
| visibility_off | Bridging the High-Frequency Data Gap: A Millisecond-Resolution Network Dataset for Advancing Time Series Foundation Models | Subina Khanal, Seshu Tirupathi, Merim Dzaferagic, Marco Ruffini, T. Pedersen | 2026-03-17 | ArXiv | 0 | 16 |
| visibility_off | FETS Benchmark: Foundation Models Outperform Dataset-specific Machine Learning in Energy Time Series Forecasting | Marco Obermeier, Marco Pruckner, Florian Haselbeck, Andreas Zeiselmair | 2026-04-24 | ArXiv | 0 | 7 |
| visibility_off | Channel-Wise Retrieval for Multivariate Time Series Forecasting | Junhyeok Kang, Jun Seo, Soyeon Park, Sangjun Han, Seohui Bae, Hyeokjun Choe, Soonyoung Lee | 2026-04-07 | ICASSP 2026 - 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | 0 | 7 |
| Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |