Time-series forecasting
This page was last updated on 2026-04-20 06:57:47 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 | 426 | 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 | 162 | 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 | ArXiv, Neural Information Processing Systems | 53 | 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. | 31 | 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 | 39 | 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 | 680 | 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 | 164 | 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 | 583 | 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 | 505 | 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 | ArXiv, International Conference on Learning Representations | 887 | 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 | 122 | 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 | 461 | 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 | 117 | 58 | open_in_new |
| visibility_off | AZ-whiteness test: a test for signal uncorrelation on spatio-temporal graphs | Daniele Zambon, C. Alippi | None | Advances in Neural Information Processing Systems 35, Neural Information Processing Systems | 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 | 97 | 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 | 2 | 10 |
| visibility_off | Pre-trained multi-scale RWKV-GCN for multivariate time series forecasting | Jianhua Hao, Fangai Liu, Weiwei Zhang | 2026-02-23 | Scientific Reports | 0 | 5 |
| 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 | 6 |
| visibility_off | TempusBench: An Evaluation Framework for Time-Series Forecasting | Denizalp Goktas, G. Riaño-Briceño, Alif 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 | 0 | 7 |
| 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 | A Survey of Deep Learning for Time Series Forecasting: Taxonomy, Analysis and Future Directions | Qi Guo, Baolin Zhao, Mingchen Song, Guoqiang Zhong | 2026-05-01 | IEEE Transactions on Knowledge and Data Engineering | 0 | 16 |
| 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 | Bi-level Heterogeneous Learning for Time Series Foundation Models: A Federated Learning Approach | Shengchao Chen, Guodong Long, Dikai Liu, Jing Jiang | 2026-04-08 | ArXiv | 0 | 36 |
| 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 | 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 | T1: One-to-One Channel-Head Binding for Multivariate Time-Series Imputation | Dong-Choon Park, Hyunwoo Ryu, S.B. Bae, Keondo Park, Hyungjoon Kim | 2026-02-24 | ArXiv | 1 | 5 |
| 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 | 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 | WaveMoE: A Wavelet-Enhanced Mixture-of-Experts Foundation Model for Time Series Forecasting | Shunyu Wu, Jiawei Huang, Weibin Feng, Boxing Li, Xiao Zhang, Erli Meng, Dan Li, Jian Lou, | 2026-04-12 | ArXiv | 0 | 7 |
| visibility_off | AI-Driven Curriculum-Learning Transformer Framework for Multivariate Time Series Forecasting | Tejas Pravinbhai Patel, Chaitanya Kulkarni, Sandeep Shivam, Chandrashekhar Medicherla, Vinay R Soni, N. Seshagiri, Isan Sahoo, Gajendra Babu Thokala | 2026-02-26 | 2026 International Seminar on Intelligent Business and Edge-Computing Research (ISIBER) | 0 | 3 |
| 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 | 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 | 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 | 5 |
| 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 | 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 | 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 | 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 | Thoth: Mid-Training Bridges LLMs to Time Series Understanding | Jia-Chun Lin, Yuxuan Wang, Jialong Wu, Huakun Luo, Zhongyi Pei, Jianmin Wang | 2026-03-01 | ArXiv | 0 | 11 |
| visibility_off | Switch-Hurdle: A MoE Encoder with AR Hurdle Decoder for Intermittent Demand Forecasting | Fabian Musat, S. Cabuz | 2026-02-26 | ArXiv | 0 | 1 |
| visibility_off | Effective Dataset Distillation for Spatio-Temporal Forecasting with Bi-dimensional Compression | Taehyung Kwon, Y. Choi, Yeongho Kim, Kijung Shin | 2026-03-11 | ArXiv | 0 | 5 |
| 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 | Time Series Foundation Models as Strong Baselines in Transportation Forecasting: A Large-Scale Benchmark Analysis | J. Pulido, Filipe Rodrigues | 2026-02-27 | ArXiv | 0 | 1 |
| visibility_off | TimeRadar: A Domain-Rotatable Foundation Model for Time Series Anomaly Detection | Hui He, Hezhe Qiao, Yutong Chen, Kun Yi, Guansong Pang | 2026-02-22 | ArXiv | 0 | 9 |
| visibility_off | Deep Learning Network-Temporal Models For Traffic Prediction | Yufeng Xin, Ethan Fan | 2026-03-12 | ArXiv | 0 | 3 |
| 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 | Multi-resolution adaptive channel fusion transformer encoder LSTM for accurate streamflow prediction | Sina Apak, Huseyin Cagan Kilinc, Adem Yurtsever, Hilal Haznedar, Furkan Ozkan | 2026-02-21 | Scientific Reports | 0 | 12 |
| 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 | 4 |
| visibility_off | Spatiotemporal System Forecasting with Irregular Time Steps via Masked Autoencoder | Kewei Zhu, Yanze Xin, Jinwei Hu, Xiaoyuan Cheng, Yiming Yang, Sibo Cheng | 2026-03-01 | Physica D: Nonlinear Phenomena | 0 | 6 |
| visibility_off | FreqCycle: A Multi-Scale Time-Frequency Analysis Method for Time Series Forecasting | Boya Zhang, Shuaijie Yin, Huiwen Zhu, Xingzuo He | 2026-03-10 | DBLP, ArXiv | 0 | 1 |
| visibility_off | Overcoming the Modality Gap in Context-Aided Forecasting | V. Zheng, 'Etienne Marcotte, Arjun Ashok, A. Williams, Lijun Sun, Alexandre Drouin, V. Zantedeschi | 2026-03-12 | ArXiv | 0 | 10 |
| 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 | 2 |
| visibility_off | Zero-shot Multivariate Time Series Forecasting Using Tabular Prior Fitted Networks | Mayuka Jayawardhana, Nihal Sharma, Kazem Meidani, B. Bruss, Tom Goldstein, Doron Bergman | 2026-04-09 | ArXiv | 0 | 13 |
| 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 | 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 | 7 |
| 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 |
| Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |