Time-series forecasting
This page was last updated on 2026-06-08 07:59:14 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 | 458 | 56 | 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 | 179 | 60 | 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 | 57 | 56 | 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 | 34 | 56 | 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 | 48 | 56 | 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 | 736 | 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 | 175 | 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 | 681 | 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 | 577 | 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 | International Conference on Learning Representations, ArXiv | 978 | 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 | Neural Information Processing Systems, ArXiv | 138 | 6 | 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 | 488 | 60 | 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 | 124 | 60 | 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 | 56 | 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 | 8 | 56 | 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 | 112 | 60 | 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 | QuITE: Query-Based Irregular Time Series Embedding | J. Lim | 2026-05-27 | ArXiv | 0 | 0 |
| visibility_off | LLM-Augmented Stiefel Graph Neural Networks for Zero-Shot Spatio-Temporal Forecasting | Jiankai Zheng, Liang Xie, Lei Zhu, Guoli Yang | 2026-07-01 | IEEE Transactions on Knowledge and Data Engineering | 0 | 3 |
| visibility_off | MixNet: A scale-adaptive method for multivariate time series forecasting | Xinhan Wang, Bowen Zhao | 2026-05-26 | PLOS One | 0 | 11 |
| visibility_off | TS-ICL: A Flexible Time-Indexed Foundation Model for Time Series via In-Context Learning | E. L. Naour, Tahar Nabil, Adrien Petralia | 2026-06-04 | ArXiv | 0 | 4 |
| visibility_off | U-STS-LLM A Unified Spatio-Temporal Steered Large Language Model for Traffic Prediction and Imputation | Yichen Zhang, Jun Li | 2026-05-12 | ArXiv | 0 | 3 |
| visibility_off | DG-LLM: Decomposition-based dynamic graph adaptation of large language models for spatiotemporal traffic forecasting | Sadia Tabassum, Naushin Nower | 2026-05-19 | PLOS One | 0 | 8 |
| visibility_off | TimeSAF: Towards LLM-Guided Semantic Asynchronous Fusion for Time Series Forecasting | Fan Zhang, Shiming Fan, Hua Wang | 2026-04-14 | ArXiv | 4 | 11 |
| 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 | 2 | 7 |
| visibility_off | NPMixer: Hierarchical Neighboring Patch Mixing for Time Series Forecasting | Jungmin Choi, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme | 2026-05-08 | ArXiv | 0 | 7 |
| visibility_off | Falcon-X: A Time Series Foundation Model for Heterogeneous Multivariate Modeling | Yiding Liu, Yifan Hu, Hongjie Xia, Peiyuan Liu, Hongzhou Chen, Xilin Dai, Zewei Dong, Jiangnan Yang | 2026-05-26 | ArXiv | 0 | 10 |
| visibility_off | HELIX: Hybrid Encoding with Learnable Identity and Cross-dimensional Synthesis for Time Series Imputation | Fengmin Zhang, Wenjie Du, Huan Zhang, Ke Yu, ShenRun Qu | 2026-05-04 | ArXiv | 0 | 4 |
| visibility_off | XCTFormer: Leveraging Cross-Channel and Cross-Time Dependencies for Enhanced Time-Series Analysis | Israel Zexer, Omri Azencot | 2026-05-18 | ArXiv | 1 | 2 |
| visibility_off | PaP-NF: Probabilistic Long-Term Time Series Forecasting via Prefix-as-Prompt Reprogramming and Normalizing Flows | Minju Kim, Youngbum Hur | 2026-05-22 | ArXiv | 0 | 6 |
| visibility_off | Reviving Error Correction in Modern Deep Time-Series Forecasting | Minh Hoang Nguyen, Dai Do, H. Nguyen, Dung Nguyen, Kien Do, Hung Le | 2026-05-20 | ArXiv | 0 | 13 |
| visibility_off | Empirical Assessment of Time-Series Foundation Models For Power System Forecasting Applications | Muhy Eddin Za’ter, B. Hodge | 2026-04-23 | ArXiv | 0 | 65 |
| 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 | KairosHope: A Next-Generation Time-Series Foundation Model for Specialized Classification via Dual-Memory Architecture | Luis Balderas, J. Rodr'iguez, Miguel Lastra, A. Arauzo-Azofra, J. M. Benítez | 2026-05-18 | ArXiv | 0 | 13 |
| visibility_off | PESD-TSF: A Period-Aware and Explicit Structured Decomposition Framework for Long-Term Time Series Forecasting | Hua Wang, Xianhao Jiao, Fan Zhang School of Computer, Artificial Intelligence, Ludong University, Yantai, Shandong 264025, China, S. O. Science, Technology, Shandong Technology, Business University, Shandong 264005 | 2026-05-15 | ArXiv | 0 | 11 |
| visibility_off | TiWeaver: Unified Temporal Dynamics Modeling via Contextual Patching | Zhe Li, Jindong Tian, Hao Miao, Zhide Lei, Chenjuan Guo, Bin Yang | 2026-06-02 | ArXiv | 0 | 43 |
| visibility_off | Mamba-Shape: A Shape-Aware Foundation Model for Time Series Classification | Sijie Liu, Jianbin Sun, Ruijing Cui, Bingyu He | 2026-04-17 | 2026 11th International Conference on Intelligent Computing and Signal Processing (ICSP) | 0 | 3 |
| visibility_off | ChronosAD: Leveraging Time Series Foundation Models for Accurate Anomaly Detection | Uzair Khan, Luigi Capogrosso, Francesco Biondani, Michele Magno, Franco Fummi, Francesco Setti, Marco Cristani | 2026-05-31 | ArXiv | 0 | 9 |
| 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 | PAMNet: Cycle-aware Phase-Amplitude Modulation Network for Multivariate Time Series Forecasting | Ying Zhou, Yutong Ye, Zhiwei Ling, Shuhao Li, Rui Qian, Jian Xiong, Li Sun, Dejing Dou | 2026-05-01 | ArXiv | 0 | 10 |
| visibility_off | Feature to Dynamics: Feature-space to Autoregression strategy for Zero-shot Time Series Forecasting | Yifan Wu, Junjie Wu, Kai Wu, Xiaoyu Zhang, Jian Lou | 2026-05-31 | ArXiv | 0 | 4 |
| 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 | 17 |
| 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 | KairosAgent: Agentic Time Series Forecasting with Fused Semantic Reasoning | Kun Feng, Ziwei Shan, Yuchen Fang, Y. Tan, Sihan Lu, Shuqi Gu, Lintao Ma, Xingyu Lu, Kan Ren | 2026-05-28 | ArXiv | 0 | 8 |
| visibility_off | AME-TS: Anchored Mixture-of-Experts for Time Series Forecasting | Rui Wang, Renhao Xue, Ray Razi, Huan Song, Hannah Marlowe | 2026-05-24 | ArXiv | 0 | 8 |
| visibility_off | PrismNet: Viewing Time Series Through a Multi-Modal Prism for Interpretable Power Load Forecasting | Yuxuan Chen, Shuo Dai, Ruoyi Xu, Haipeng Xie | 2026-05-09 | ArXiv | 0 | 3 |
| visibility_off | Unicorn: Scaling High-Dimensional Time Series Forecasting via Universal Correlation Modeling | Haochen Yuan, Yichen Song, Yunbo Wang, Xiaokang Yang | 2026-05-26 | ArXiv | 0 | 11 |
| visibility_off | Factorize to Generalize: Retrieval-Guided Invariant-Dynamic Decomposition for Time Series Forecasting | Jinjin Chi, Lei Feng, Lulu Zhang, Yongcheng Jing, Yiming Wang, Ximing Li, Jialie Shen, Leszek Rutkowski, Dacheng Tao | 2026-05-24 | ArXiv | 0 | 12 |
| visibility_off | Why Do Time Series Models Need Long Context Windows? | L. Butera, G. Felice, Andrea Cini, C. Alippi | 2026-06-01 | ArXiv | 0 | 56 |
| visibility_off | A Simple State Space Model Excels at Multivariate Time Series Classification | Hassan Saadatmand, Geoffrey I. Webb, Hamid Rezatofighi, Mahsa Salehi | 2026-05-07 | ArXiv | 0 | 5 |
| visibility_off | DecompKAN: Decomposed Patch-KAN for Long-Term Time Series Forecasting | N. Mysore | 2026-04-27 | ArXiv | 1 | 8 |
| visibility_off | Assessing the Operational Viability of Foundation Models for Time Series Forecasting | Kavin k. Soni, Debanshu Das, Vamshidhar Guduguntla | 2026-05-23 | ArXiv | 0 | 3 |
| 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 | 4 | 20 |
| visibility_off | Progressive Spatiotemporal Graph Modeling for Spacecraft Anomaly Detection | Zihan Chen, Zewen Li, Yuge Cao, Yue Wang, Hsi Chang | 2026-04-01 | Entropy | 0 | 4 |
| visibility_off | What If We Let Forecasting Forget? A Sparse Bottleneck for Cross-Variable Dependencies | Fangzhao Zhang, Shiming Fan, Hua Wang | 2026-05-08 | ArXiv | 0 | 5 |
| visibility_off | Generalizing Multi-Scale Time-Series Modeling with a Single Operator | Cheonwoo Lee, Dooho Lee, Doyun Choi, Jaemin Yoo | 2026-05-29 | ArXiv | 0 | 1 |
| 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 | 1 |
| visibility_off | TimeTok: Granularity-Controllable Time-Series Generation via Hierarchical Tokenization | Seokhyun Lee, Jaeho Kim, Chan-Su Oh, M. Schaar, Changhee Lee | 2026-05-02 | ArXiv | 0 | 76 |
| visibility_off | Multimodal Fusion for Time Series Forecasting: Learning from Temporal and Visual Data | J. Oliveira, Patrícia Ramos | 2026-05-08 | 2026 IEEE Conference on Artificial Intelligence (CAI) | 0 | 8 |
| visibility_off | Optimized Gaussian Large Language Model (LLM) Reprogrammed for Temporal Predictions | S. Stefenon, J. Matos-Carvalho, L. O. Seman, V. Leithardt, K. Yow | 2026-06-15 | 2026 22nd International Conference on Intelligent Environments (IE) | 0 | 36 |
| visibility_off | ChronoVAE-HOPE: Beyond Attention -- A Next-Generation VAE Foundation Model for Specialized Time Series Classification | J. Rodr'iguez, Luis Balderas, Miguel Lastra, A. Arauzo-Azofra, J. M. Benítez | 2026-05-21 | ArXiv | 0 | 13 |
| Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |