Time-series forecasting
This page was last updated on 2024-09-16 06:06:16 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 | 65 | 50 | 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 | 75 | 47 | 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 | 18 | 50 | 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 | 12 | 50 | open_in_new |
| visibility_off | Graph Deep Learning for Time Series Forecasting | Andrea Cini, Ivan Marisca, Daniele Zambon, C. Alippi | 2023-10-24 | ArXiv, arXiv.org | 6 | 50 | 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 | 131 | 14 | open_in_new |
| visibility_off | Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces | Chloe X. Wang, Oleksii Tsepa, Jun Ma, Bo Wang | 2024-02-01 | ArXiv, arXiv.org | 50 | 5 | 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 | ArXiv, International Conference on Machine Learning | 54 | 14 | 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 | ArXiv, International Conference on Machine Learning | 32 | 22 | 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 | 136 | 9 | 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, arXiv.org | 2 | 2 | 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 | 178 | 47 | 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 | 27 | 47 | open_in_new |
| visibility_off | AZ-whiteness test: a test for signal uncorrelation on spatio-temporal graphs | Daniele Zambon, C. Alippi | None | DBLP | 6 | 50 | open_in_new |
| visibility_off | Graph state-space models | Daniele Zambon, Andrea Cini, L. Livi, C. Alippi | 2023-01-04 | ArXiv, arXiv.org | 4 | 50 | 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 | ArXiv | 2 | 47 | 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 | Reprogramming Foundational Large Language Models(LLMs) for Enterprise Adoption for Spatio-Temporal Forecasting Applications: Unveiling a New Era in Copilot-Guided Cross-Modal Time Series Representation Learning | Sakhinana Sagar Srinivas, Chidaksh Ravuru, Geethan Sannidhi, Venkataramana Runkana | 2024-08-26 | ArXiv | 0 | 3 |
| visibility_off | LeRet: Language-Empowered Retentive Network for Time Series Forecasting | Qihe Huang, Zhen-Qiang Zhou, Kuo Yang, Gengyu Lin, Zhongchao Yi, Yang Wang | 2024-08-01 | Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence | 0 | 3 |
| visibility_off | TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model | Defu Cao, Wen Ye, Yizhou Zhang, Yan Liu | 2024-09-03 | ArXiv | 0 | 9 |
| visibility_off | PRformer: Pyramidal Recurrent Transformer for Multivariate Time Series Forecasting | Yongbo Yu, Weizhong Yu, Feiping Nie, Xuelong Li | 2024-08-20 | ArXiv | 0 | 10 |
| visibility_off | A federated large language model for long-term time series forecasting | Raed Abdel Sater, A. B. Hamza | 2024-07-30 | ArXiv | 0 | 1 |
| visibility_off | Simplified Mamba with Disentangled Dependency Encoding for Long-Term Time Series Forecasting | Zixuan Weng, Jindong Han, Wenzhao Jiang, Hao Liu | 2024-08-22 | ArXiv | 0 | 10 |
| visibility_off | Skip-Timeformer: Skip-Time Interaction Transformer for Long Sequence Time-Series Forecasting | Wenchang Zhang, Hua Wang, Fan Zhang | 2024-08-01 | Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence | 0 | 4 |
| visibility_off | PLUTUS: A Well Pre-trained Large Unified Transformer can Unveil Financial Time Series Regularities | Yuanjian Xu, Anxian Liu, Jianing Hao, Zhenzhuo Li, Shichang Meng, Guang Zhang | 2024-08-19 | ArXiv | 0 | 0 |
| visibility_off | Agentic Retrieval-Augmented Generation for Time Series Analysis | Chidaksh Ravuru, Sagar Srinivas Sakhinana, Venkataramana Runkana | 2024-08-18 | ArXiv | 0 | 3 |
| visibility_off | Decoupled Invariant Attention Network for Multivariate Time-series Forecasting | Haihua Xu, Wei Fan, Kun Yi, Pengyang Wang | 2024-08-01 | Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence | 0 | 4 |
| visibility_off | Scalable Transformer for High Dimensional Multivariate Time Series Forecasting | Xin Zhou, Weiqing Wang, W. Buntine, Shilin Qu, Abishek Sriramulu, Weicong Tan, Christoph Bergmeir | 2024-08-08 | ArXiv | 0 | 16 |
| visibility_off | AutoCTS++: zero-shot joint neural architecture and hyperparameter search for correlated time series forecasting | Xinle Wu, Xingjian Wu, Bin Yang, Lekui Zhou, Chenjuan Guo, Xiangfei Qiu, Jilin Hu, Zhenli Sheng, Christian S. Jensen | 2024-07-30 | VLDB J. | 0 | 27 |
| visibility_off | Spatial–Temporal Transformer Networks for Traffic Flow Forecasting Using a Pre-Trained Language Model | Ju Ma, Juan Zhao, Yao Hou | 2024-08-25 | Sensors (Basel, Switzerland) | 0 | 0 |
| visibility_off | Time Series Foundation Models and Deep Learning Architectures for Earthquake Temporal and Spatial Nowcasting | Alireza Jafari, Geoffrey C. Fox, John B. Rundle, A. Donnellan, L. G. Ludwig | 2024-08-21 | ArXiv | 0 | 31 |
| visibility_off | sTransformer: A Modular Approach for Extracting Inter-Sequential and Temporal Information for Time-Series Forecasting | Jiaheng Yin, Zhengxin Shi, Jianshen Zhang, Xiaoming Lin, Yulin Huang, Yongzhi Qi, Wei Qi | 2024-08-19 | ArXiv | 0 | 2 |
| visibility_off | Unleash The Power of Pre-Trained Language Models for Irregularly Sampled Time Series | Weijiao Zhang, Chenlong Yin, Hao Liu, Hui Xiong | 2024-08-12 | ArXiv | 0 | 6 |
| visibility_off | DRFormer: Multi-Scale Transformer Utilizing Diverse Receptive Fields for Long Time-Series Forecasting | Ruixin Ding, Yuqi Chen, Yu-Ting Lan, Wei Zhang | 2024-08-05 | ArXiv | 0 | 0 |
| visibility_off | VE: Modeling Multivariate Time Series Correlation with Variate Embedding | Shangjiong Wang, Zhihong Man, Zhengwei Cao, Jinchuan Zheng, Zhikang Ge | 2024-09-10 | ArXiv | 0 | 3 |
| visibility_off | DAM: Towards A Foundation Model for Time Series Forecasting | Luke Darlow, Qiwen Deng, Ahmed Hassan, Martin Asenov, Rajkarn Singh, Artjom Joosen, Adam Barker, A. Storkey | 2024-07-25 | ArXiv | 0 | 43 |
| visibility_off | Mamba or Transformer for Time Series Forecasting? Mixture of Universals (MoU) Is All You Need | Sijia Peng, Yun Xiong, Yangyong Zhu, Zhiqiang Shen | 2024-08-28 | ArXiv | 0 | 19 |
| visibility_off | FMamba: Mamba based on Fast-attention for Multivariate Time-series Forecasting | Shusen Ma, Yu Kang, Peng Bai, Yunan Zhao | 2024-07-20 | ArXiv | 0 | 1 |
| visibility_off | DTFormer: A Transformer-Based Method for Discrete-Time Dynamic Graph Representation Learning | Xi Chen, Yun Xiong, Siwei Zhang, Jiawei Zhang, Yao Zhang, Shiyang Zhou, Xixi Wu, Mingyang Zhang, Tengfei Liu, Weiqiang Wang | 2024-07-26 | ArXiv | 0 | 4 |
| visibility_off | Unlocking the Power of LSTM for Long Term Time Series Forecasting | Yaxuan Kong, Zepu Wang, Yuqi Nie, Tian Zhou, Stefan Zohren, Yuxuan Liang, Peng Sun, Qingsong Wen | 2024-08-19 | ArXiv | 0 | 5 |
| visibility_off | Multiscale Representation Enhanced Temporal Flow Fusion Model for Long-Term Workload Forecasting | Shiyu Wang, Zhixuan Chu, Yinbo Sun, Yu Liu, Yuliang Guo, Yang Chen, Huiyang Jian, Lintao Ma, Xingyu Lu, Jun Zhou | 2024-07-29 | ArXiv | 0 | 4 |
| visibility_off | An NCDE-based Framework for Universal Representation Learning of Time Series | Zihang Liu, Bowen Du, Junchen Ye, Xianqing Wen, Leilei Sun | 2024-08-01 | Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence | 0 | 26 |
| visibility_off | An Evaluation of Standard Statistical Models and LLMs on Time Series Forecasting | Rui Cao, Qiao Wang | 2024-08-09 | ArXiv | 0 | 3 |
| visibility_off | MedTsLLM: Leveraging LLMs for Multimodal Medical Time Series Analysis | Nimeesha Chan, Felix Parker, William Bennett, Tianyi Wu, Mung Yao Jia, James Fackler, Kimia Ghobadi | 2024-08-14 | ArXiv | 0 | 1 |
| visibility_off | SDformer: Transformer with Spectral Filter and Dynamic Attention for Multivariate Time Series Long-term Forecasting | Ziyu Zhou, Gengyu Lyu, Yiming Huang, Zihao Wang, Ziyu Jia, Zhen Yang | 2024-08-01 | Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence | 0 | 11 |
| visibility_off | TempoKGAT: A Novel Graph Attention Network Approach for Temporal Graph Analysis | L. Sasal, Daniel Busby, Abdenour Hadid | 2024-08-29 | ArXiv | 0 | 2 |
| visibility_off | Heterogeneous Graph Transformer with Poly-Tokenization | Zhiyuan Lu, Yuan Fang, Cheng Yang, Chuan Shi | 2024-08-01 | Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence | 1 | 4 |
| visibility_off | TCNFormer: Temporal Convolutional Network Former for Short-Term Wind Speed Forecasting | Abid Hasan Zim, Aquib Iqbal, Asad Malik, Zhicheng Dong, Hanzhou Wu | 2024-08-27 | ArXiv | 0 | 2 |
| visibility_off | DLFormer: Enhancing Explainability in Multivariate Time Series Forecasting using Distributed Lag Embedding | Younghwi Kim, Dohee Kim, Sunghyun Sim | 2024-08-29 | ArXiv | 0 | 4 |
| visibility_off | Forecast-PEFT: Parameter-Efficient Fine-Tuning for Pre-trained Motion Forecasting Models | Jifeng Wang, Kaouther Messaoud, Yuejiang Liu, Juergen Gall, Alexandre Alahi | 2024-07-28 | ArXiv | 0 | 11 |
| visibility_off | Multi-Scale Spatio-Temporal Attention Networks for Network-Scale Traffic Learning and Forecasting | Cong Wu, Hui Ding, Zhongwang Fu, Ning Sun | 2024-08-27 | Sensors (Basel, Switzerland) | 0 | 2 |
| visibility_off | Multi-View Neural Differential Equations for Continuous-Time Stream Data in Long-Term Traffic Forecasting | Zibo Liu, Zhe Jiang, Shigang Chen | 2024-08-12 | ArXiv | 0 | 2 |
| visibility_off | Contrastive Representation Learning for Dynamic Link Prediction in Temporal Networks | Amirhossein Nouranizadeh, Fatemeh Tabatabaei Far, Mohammad Rahmati | 2024-08-22 | ArXiv | 0 | 2 |
| visibility_off | DSTLNet: Dynamic Spatial-Temporal Correlation Learning Network for Traffic Sensor Signal Prediction | Yuxiang Shan, Hailiang Lu, Weidong Lou | 2024-08-08 | Sensors and Materials | 0 | 3 |
| visibility_off | Survey and Taxonomy: The Role of Data-Centric AI in Transformer-Based Time Series Forecasting | Jingjing Xu, Caesar Wu, Yuan-Fang Li, Grégoire Danoy, Pascal Bouvry | 2024-07-29 | ArXiv | 0 | 23 |
| visibility_off | Layerwise Recurrent Router for Mixture-of-Experts | Zihan Qiu, Zeyu Huang, Shuang Cheng, Yizhi Zhou, Zili Wang, Ivan Titov, Jie Fu | 2024-08-13 | ArXiv | 0 | 3 |
| visibility_off | Linear Attention is Enough in Spatial-Temporal Forecasting | Xinyu Ning | 2024-08-17 | ArXiv | 0 | 0 |
| visibility_off | SpecAR-Net: Spectrogram Analysis and Representation Network for Time Series | Yi Dong, Liwen Zhang, Youcheng Zhang, Shi Peng, Wen Chen, Zhe Ma | 2024-08-01 | Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence | 0 | 0 |
| visibility_off | An Evaluation of Deep Learning Models for Stock Market Trend Prediction | Gonzalo Lopez Gil, Paul Duhamel-Sebline, Andrew McCarren | 2024-08-22 | ArXiv | 0 | 0 |
| visibility_off | SCAT: A Time Series Forecasting with Spectral Central Alternating Transformers | Chengjie Zhou, Chao Che, Pengfei Wang, Qiang Zhang | 2024-08-01 | Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence | 0 | 8 |
| visibility_off | Pre-DyGAE: Pre-training Enhanced Dynamic Graph Autoencoder for Occupational Skill Demand Forecasting | Xi Chen, Chuan Qin, Zhigaoyuan Wang, Yihang Cheng, Chao Wang, Hengshu Zhu, Hui Xiong | 2024-08-01 | Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence | 1 | 3 |
| visibility_off | KAN4TSF: Are KAN and KAN-based models Effective for Time Series Forecasting? | Xiao Han, Xinfeng Zhang, Yiling Wu, Zhenduo Zhang, Zhe Wu | 2024-08-21 | ArXiv | 0 | 1 |
| Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |