Time-series forecasting
This page was last updated on 2026-07-20 07:17:07 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 | 498 | 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 | ArXiv, International Conference on Learning Representations | 182 | 62 | 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 | 57 | 56 | 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. | 35 | 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 | 50 | 56 | open_in_new |
| visibility_off | Large Language Models Are Zero-Shot Time Series Forecasters | N. Gruver, Marc Finzi, Shikai Qiu, Andrew Gordon Wilson | 2023-10-11 | ArXiv, Neural Information Processing Systems | 787 | 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 | 185 | 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 | 781 | 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 | 654 | 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 | 1069 | 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, A. Jati, Nam H. Nguyen, Pankaj Dayama, Chandra Reddy, Wesley M. Gifford, Jayant Kalagnanam | 2024-01-08 | ArXiv, Neural Information Processing Systems | 160 | 14 | 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 | 507 | 62 | 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 | 134 | 62 | 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 | 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 | Advances in Neural Information Processing Systems 37, Neural Information Processing Systems | 126 | 62 | 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 | A survey of deep time series forecasting backbone architectures: progress, pitfalls, and a systematic comparison | Xiang Li, Yanping Zheng, Zhewei Wei | 2026-07-08 | Frontiers of Computer Science | 0 | 6 |
| 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 | LLM4Imp: Leveraging Frozen Large Language Models with Spectral Prompts for Time-Series Imputation | Franck Junior Aboya Messou, Jinhua Chen, Tong Liu, Shilong Zhang, Weiyu Wang, Tao Yu, Keping Yu | 2026-05-24 | ICC 2026 - IEEE International Conference on Communications | 0 | 5 |
| 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 | 1 | 10 |
| 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 | Extreme Adaptive Transformer for Time Series Forecasting | Sanjeev Shrestha, Hui Liu, Yifan Zhang | 2026-07-02 | ArXiv | 0 | 4 |
| visibility_off | VFEM: Visual Feature Empowered Multivariate Time Series Forecasting with Cross-Modal Fusion | Yanlong Wang, Hang Yu, Jian Xu, Fei Ma, Hongkang Zhang, Tongtong Feng, Zijian Zhang, Shao-Lun Huang, Dan Sun, Xiao-Ping Zhang | 2025-09-25 | Trans. Mach. Learn. Res. | 0 | 8 |
| visibility_off | DFG-PatchTST: a dynamic fusion gated patch transformer for multicomponent time series forecasting | Yunsen Zhou, Yinxin Bao, Quan Shi | 2026-07-01 | Applied Intelligence | 0 | 7 |
| visibility_off | TFAF: Temporal-Frequency Attention Fusion for Transformer Pretraining in Time Series Forecasting | Weisen Cheng, Ming Xue, Binchuan Zhang, Lu Zhang, Pengfei Wang, Xiaofei Yang, Yudong Fang, Jing Li | 2026-05-24 | 2026 IEEE International Symposium on Circuits and Systems (ISCAS) | 0 | 7 |
| visibility_off | Sample-efficient fine-tuning with textual prompts for time series forecasting | Kaibin Wei, Jianqiang Jing, Jiawei Liu, Qing Liu, Xiannian Xie | 2026-07-08 | PLOS One | 0 | 3 |
| visibility_off | ADyTNet: Learning Time‐Aware Dynamic Graphs and Tri‐Band Temporal Pattern for Multivariate Time Series Forecasting | Weigang Huo, Yudong Bai, Yinan Wang | 2026-06-01 | Concurrency and Computation: Practice and Experience | 0 | 3 |
| visibility_off | One Step Closer to Ground Truth: A Multi-Scale Residual-Aware Representation Learning Pipeline for Predicting Time Series Data | Amrijit Biswas, Mustafa Kamal, Robin Krambroeckers, M. M. L. Elahi, Sifat Momen, Nabeel Mohammed, S. Rahman | 2026-06-09 | ArXiv | 0 | 18 |
| visibility_off | Distribution-Aware Diffusion-LLM for Robust Ultra-Long-Term Time Series Forecasting | Falguni Ghosh, Vahid Hashemi, Bernhard Kainz | 2026-06-22 | ArXiv | 0 | 2 |
| visibility_off | Understanding Key Features of Time Series Foundation Models from Epidemic Forecasting | Alireza Jafari, Judy Fox, Geoffrey C. Fox, M. Marathe, A. Adiga | 2026-06-17 | ArXiv | 0 | 58 |
| visibility_off | TimEE: End-to-end Time Series Classification via In-Context Learning | Jaris Kuken, Shi Bin Hoo, M. Mráz, Frank Hutter, Lennart Purucker | 2026-07-08 | ArXiv | 0 | 10 |
| 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 | Time-Series Foundation Model Embeddings for Remaining Useful Life Estimation | Amir El-Ghoussani, Michele De Vita, Ronald Naumann, Valiseios Belagiannis | 2026-06-10 | ArXiv | 1 | 3 |
| visibility_off | CITRAS-FM: Tiny Time Series Foundation Model for Covariate-Informed Zero-Shot Forecasting | Yosuke Yamaguchi, Issei Suemitsu, Yuki Kajihara, Wenpeng Wei | 2026-06-09 | ArXiv | 0 | 5 |
| 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 | Learning a Causation-Driven Retrieval Model for Effective Time Series Augmentation and Forecasting | Bohan Zhang, Dixin Luo | 2026-08-01 | IEEE Transactions on Knowledge and Data Engineering | 0 | 11 |
| visibility_off | PMDformer: Patch-Mean Decoupling Information Transformer for Long-term Forecasting | Ao Hu, Liangjian Wen, Jiang Duan, Yong Dai, He Yan, Dongkai Wang, Jun Wang, Yukun Zhang, Ruoxi Jiang, Zenglin Xu | 2026-06-25 | ArXiv | 0 | 7 |
| 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 | 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 | STaT: Resolving Shape Distortion in Non-Stationary Time Series via Tri-Modal Synergy | Huiping Cheng, Jinsheng Guo, Zhenhao Weng, Yan Qiao, Meng Li | 2026-05-25 | ArXiv | 0 | 2 |
| visibility_off | STKAN: Kolmogorov-Arnold Networks for Spatio-Temporal Forecasting | Sicong Lai, Yuehong Hu, Siru Zhong, Sichao Qiao, Yuxuan Liang, Guangyin Jin | 2026-07-14 | ArXiv | 0 | 9 |
| visibility_off | Learning the Context of Errors: Black-Box Online Adaptation of Time Series Foundation Models | Xilin Dai, Yiding Liu, Hongjie Xia, Yifan Hu, Zewei Dong, Jiangnan Yang, Qiang Xu | 2026-06-12 | ArXiv | 0 | 17 |
| visibility_off | Speaking Numbers to LLMs: Multi-Wavelet Number Embeddings for Time Series Forecasting | Defu Cao, Zijie Lei, Muyan Weng, Jiao Sun, Yan Liu | 2026-06-25 | ArXiv | 2 | 14 |
| visibility_off | Why Do Time Series Models Need Long Context Windows? | L. Butera, G. Felice, Andrea Cini, C. Alippi | 2026-06-01 | ArXiv | 1 | 56 |
| visibility_off | EMD-based combined attention mechanism RNN for multivariate time series forecasting | Wei-feng Ding, Chunxia Zhang, Huachuan Huang, Zizhao Guo, Lihong Long, Nannan Ji | 2026-05-30 | Applied Intelligence | 0 | 10 |
| visibility_off | Self-Gating Attention for Efficient Time Series Forecasting | Dezheng Wang, Tong Chen, Wei Yuan, Congyan Chen, Shihua Li, Hongzhi Yin | 2026-07-02 | ArXiv | 0 | 15 |
| visibility_off | Hybrid diffusion-xLSTM framework for time-series prediction | Sarinna Maplook, Koji Eguchi | 2026-05-30 | International Journal of Data Science and Analytics | 0 | 1 |
| 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 | EvoTS: Evolutionary Transformer Search for Time Series Forecasting | A. Elsaid, Damir Pulatov | 2026-06-30 | Proceedings of the Genetic and Evolutionary Computation Conference | 0 | 12 |
| visibility_off | DEMamba: Decoupled Enhanced State Space Models with Selective Mechanisms for Multivariate Time Series Forecasting | Junluo Zheng, Yang Liu, Jianyong Chen | 2026-05-25 | Proc. of the 25th International Conference on Autonomous Agents and Multiagent Systems | 1 | 3 |
| visibility_off | MambaAir: a multi-scale hybrid mamba-attention model for air quality prediction | Chunyan Kan, Dong Zhao, Wei Song | 2026-06-15 | Pattern Analysis and Applications | 0 | 6 |
| visibility_off | FGSNN: a FusionGraphSAGE with neural networks for traffic flow prediction | Yanan Chen, Yongmei Ma, Shuchao Wang, Yunbiao Wu, Yong Zhou, Zhixin Chen, Weicai Peng | 2026-07-01 | The Journal of Supercomputing | 0 | 0 |
| visibility_off | An Adaptive Routing-Based LSTM-Informer Fusion Model and Its Application in Time Series Forecasting | Jiaqiang Chen, Yuze Li, Zhijie Li, Jian Zhang | 2026-05-22 | 2026 5th Conference on Fully Actuated System Theory and Applications (FASTA) | 0 | 7 |
| visibility_off | Spectral Retrieval-Augmented Time-Series Forecasting | H. Nguyen, M. Nguyen, Dung Nguyen, Hung Le | 2026-06-17 | ArXiv | 0 | 3 |
| 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 | Pretrained Time-Series Foundation Models for Financial Return Forecasting | M. N. I. Alonso, Rodolfo Pereira Franklin | 2026-06-25 | ArXiv | 0 | 2 |
| visibility_off | GlucoFM-Bench: Benchmarking Time-Series Foundation Models for Blood Glucose Forecasting | Baiying Lu, Zhaohui Liang, Ryan Pontius, Shengpu Tang, T. Prioleau | 2026-06-05 | ArXiv | 0 | 14 |
| Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |