Time-series forecasting
This page was last updated on 2025-01-13 06:05:50 UTC
Manually curated articles on Time-series forecasting
Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index | View recommendations |
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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 | 92 | 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 | 94 | 48 | 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 | 24 | 50 | 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. | 14 | 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 | 9 | 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 | ArXiv, Neural Information Processing Systems | 214 | 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 | 62 | 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 | 121 | 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 | 83 | 25 | 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 | 217 | 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 | 4 | 4 | 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 | 224 | 48 | 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 | ArXiv, DBLP | 44 | 48 | 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 | 4 | 48 | 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 |
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visibility_off | WaveGNN: Modeling Irregular Multivariate Time Series for Accurate Predictions | Arash Hajisafi, M. Siampou, Bita Azarijoo, Cyrus Shahabi | 2024-12-14 | ArXiv | 0 | 3 |
visibility_off | UTSD: Unified Time Series Diffusion Model | Xiangkai Ma, Xiaobin Hong, Wenzhong Li, Sanglu Lu | 2024-12-04 | ArXiv | 0 | 3 |
visibility_off | Knowledge-enhanced Transformer for Multivariate Long Sequence Time-series Forecasting | S. T. Kakde, Rony Mitra, Jasashwi Mandal, Manoj Kumar Tiwari | 2024-11-17 | ArXiv | 0 | 5 |
visibility_off | In-Depth Review of Neural Network Architectures for Forecasting Heart Rate Time Series Data | Ekaterina Popovska-Slavova, G. Georgieva-Tsaneva | 2024-12-20 | Innovative STEM Education | 0 | 7 |
visibility_off | ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual Data | Chengsen Wang, Qi Qi, Jingyu Wang, Haifeng Sun, Zirui Zhuang, Jinming Wu, Lei Zhang, Jianxin Liao | 2024-12-16 | ArXiv | 0 | 27 |
visibility_off | A Wave is Worth 100 Words: Investigating Cross-Domain Transferability in Time Series | Xiangkai Ma, Xiaobin Hong, Wenzhong Li, Sanglu Lu | 2024-12-01 | ArXiv | 0 | 3 |
visibility_off | TimeCHEAT: A Channel Harmony Strategy for Irregularly Sampled Multivariate Time Series Analysis | Jiexi Liu, Meng Cao, Songcan Chen | 2024-12-17 | ArXiv | 0 | 2 |
visibility_off | PreMixer: MLP-Based Pre-training Enhanced MLP-Mixers for Large-scale Traffic Forecasting | Tongtong Zhang, Zhiyong Cui, Bingzhang Wang, Yilong Ren, Haiyang Yu, Pan Deng, Yinhai Wang | 2024-12-18 | ArXiv | 0 | 3 |
visibility_off | Ister: Inverted Seasonal-Trend Decomposition Transformer for Explainable Multivariate Time Series Forecasting | Fanpu Cao, Shu Yang, Zhengjian Chen, Ye Liu, Laizhong Cui | 2024-12-25 | ArXiv | 0 | 0 |
visibility_off | MFF-FTNet: Multi-scale Feature Fusion across Frequency and Temporal Domains for Time Series Forecasting | Yangyang Shi, Qianqian Ren, Yong Liu, Jianguo Sun | 2024-11-26 | ArXiv | 0 | 0 |
visibility_off | LMS-AutoTSF: Learnable Multi-Scale Decomposition and Integrated Autocorrelation for Time Series Forecasting | Ibrahim Delibasoglu, Sanjay Chakraborty, Fredrik Heintz | 2024-12-09 | ArXiv | 0 | 5 |
visibility_off | Zero-Shot Load Forecasting with Large Language Models | Wenlong Liao, Zhe Yang, Mengshuo Jia, Christian Rehtanz, Jiannong Fang, Fernando Port'e-Agel | 2024-11-18 | ArXiv | 0 | 6 |
visibility_off | Generalized Prompt Tuning: Adapting Frozen Univariate Time Series Foundation Models for Multivariate Healthcare Time Series | Mingzhu Liu, Angela H. Chen, George H. Chen | 2024-11-19 | ArXiv | 0 | 0 |
visibility_off | Learning Latent Spaces for Domain Generalization in Time Series Forecasting | Songgaojun Deng, M. D. Rijke | 2024-12-15 | ArXiv | 0 | 14 |
visibility_off | xPatch: Dual-Stream Time Series Forecasting with Exponential Seasonal-Trend Decomposition | Artyom Stitsyuk, Jaesik Choi | 2024-12-23 | ArXiv | 0 | 1 |
visibility_off | Best of Both Worlds: Advantages of Hybrid Graph Sequence Models | Ali Behrouz, Ali Parviz, Mahdi Karami, Clayton Sanford, Bryan Perozzi, V. Mirrokni | 2024-11-23 | ArXiv | 0 | 56 |
visibility_off | DSSRNN: Decomposition-Enhanced State-Space Recurrent Neural Network for Time-Series Analysis | Ahmad Mohammadshirazi, Ali Nosratifiroozsalari, R. Ramnath | 2024-12-01 | ArXiv | 0 | 23 |
visibility_off | MuSiCNet: A Gradual Coarse-to-Fine Framework for Irregularly Sampled Multivariate Time Series Analysis | Jiexi Liu, Meng Cao, Songcan Chen | 2024-12-02 | ArXiv | 0 | 2 |
visibility_off | Bridging Simplicity and Sophistication using GLinear: A Novel Architecture for Enhanced Time Series Prediction | Syed Tahir Hussain Rizvi, Neel Kanwal, Muddasar Naeem, Alfredo Cuzzocrea, Antonio Coronato | 2025-01-02 | ArXiv | 0 | 12 |
visibility_off | TableTime: Reformulating Time Series Classification as Zero-Shot Table Understanding via Large Language Models | Jiahao Wang, Mingyue Cheng, Qingyang Mao, Qi Liu, Feiyang Xu, Xin Li, Enhong Chen | 2024-11-24 | ArXiv | 1 | 12 |
visibility_off | Spatio-Temporal Forecasting of PM2.5 via Spatial-Diffusion guided Encoder-Decoder Architecture | Malay Pandey, Vaishali Jain, Nimit Godhani, S. N. Tripathi, Piyush Rai | 2024-12-18 | ArXiv | 0 | 35 |
visibility_off | How Much Can Time-related Features Enhance Time Series Forecasting? | Chaolv Zeng, Yuan Tian, Guanjie Zheng, Yunjun Gao | 2024-12-02 | ArXiv | 0 | 2 |
visibility_off | Multi-Granularity Temporal Embedding Transformer Network for Traffic Flow Forecasting | Jiani Huang, He Yan, Qixiu Chen, Yingan Liu | 2024-12-01 | Sensors (Basel, Switzerland) | 0 | 1 |
visibility_off | From RNNs to Foundation Models: An Empirical Study on Commercial Building Energy Consumption | Shourya Bose, Yijiang Li, Amy Van Sant, Yu Zhang, Kibaek Kim | 2024-11-21 | ArXiv | 0 | 3 |
visibility_off | Disentangled Interpretable Representation for Efficient Long-term Time Series Forecasting | Yuang Zhao, Tianyu Li, Jiadong Chen, Shenrong Ye, Fuxin Jiang, Tieying Zhang, Xiaofeng Gao | 2024-11-26 | ArXiv | 0 | 1 |
visibility_off | Unveiling the Inflexibility of Adaptive Embedding in Traffic Forecasting | Hongjun Wang, Jiyuan Chen, Lingyu Zhang, Renhe Jiang, Xuan Song | 2024-11-18 | ArXiv | 0 | 19 |
visibility_off | HiMoE: Heterogeneity-Informed Mixture-of-Experts for Fair Spatial-Temporal Forecasting | Shaohan Yu, Pan Deng, Yu Zhao, Junting Liu, Zi'ang Wang | 2024-11-30 | ArXiv | 0 | 4 |
visibility_off | QuLTSF: Long-Term Time Series Forecasting with Quantum Machine Learning | Hari Hara Suthan Chittoor, Paul Robert Griffin, Ariel Neufeld, Jayne Thompson, Mile Gu | 2024-12-18 | ArXiv | 0 | 20 |
visibility_off | GG-SSMs: Graph-Generating State Space Models | Nikola Zubic, Davide Scaramuzza | 2024-12-17 | ArXiv | 0 | 4 |
visibility_off | Clustering Time Series Data with Gaussian Mixture Embeddings in a Graph Autoencoder Framework | Amirabbas Afzali, Hesam Hosseini, Mohmmadamin Mirzai, Arash Amini | 2024-11-25 | ArXiv | 0 | 0 |
visibility_off | Tackling Data Heterogeneity in Federated Time Series Forecasting | Wei Yuan, Guanhua Ye, Xiangyu Zhao, Quoc Viet Hung Nguyen, Yang Cao, Hongzhi Yin | 2024-11-24 | ArXiv | 0 | 9 |
visibility_off | A Comparative Study of Pruning Methods in Transformer-based Time Series Forecasting | Nicholas Kiefer, Arvid Weyrauch, Muhammed Oz, Achim Streit, Markus Gotz, Charlotte Debus | 2024-12-17 | ArXiv | 0 | 4 |
visibility_off | Partial Transfer Learning from Patch Transformer to Variate-Based Linear Forecasting Model | L. Anh, D. Vu, Seungmin Oh, Gwanghyun Yu, Nguyen Bui Ngoc Han, Hyoung‐Gook Kim, Jin-Sul Kim, Jin-Young Kim | 2024-12-21 | Energies | 0 | 15 |
visibility_off | FSMLP: Modelling Channel Dependencies With Simplex Theory Based Multi-Layer Perceptions In Frequency Domain | Zhengnan Li, Haoxuan Li, Hao Wang, Jun Fang, Duoyin Li Yunxiao Qin | 2024-12-02 | ArXiv | 0 | 2 |
visibility_off | MSAF: A Multi-Scale Attention-Fusion Model for Long-Term Cell-Level Network Traffic Prediction | Xuesen Ma, Jingqi Li, Dacheng Li, Yangyu Li, Yan Qiao | 2024-11-23 | 2024 6th International Conference on Electrical, Control and Instrumentation Engineering (ICECIE) | 0 | 1 |
visibility_off | Content-aware Balanced Spectrum Encoding in Masked Modeling for Time Series Classification | Yudong Han, Haocong Wang, Yupeng Hu, Yongshun Gong, Xuemeng Song, Weili Guan | 2024-12-17 | ArXiv | 0 | 2 |
visibility_off | Breaking the Context Bottleneck on Long Time Series Forecasting | Chao Ma, Yikai Hou, Xiang Li, Yinggang Sun, Haining Yu, Zhou Fang, Jiaxing Qu | 2024-12-21 | ArXiv | 0 | 4 |
visibility_off | TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation | Si-Nan Yang, Dong Wang, Haoqi Zheng, Ruochun Jin | 2024-12-21 | ArXiv | 0 | 0 |
visibility_off | Forecasting Influenza Like Illness based on White-Box Transformers | Rujia Shen, Yaoxiong Lin, Boran Wang, Liangliang Liu, Yi Guan, Jingchi Jiang | 2024-12-03 | 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) | 0 | 11 |
visibility_off | On the Feasibility of Vision-Language Models for Time-Series Classification | Vinay Prithyani, Mohsin Mohammed, Richa Gadgil, Ricardo Buitrago, Vinija Jain, Aman Chadha | 2024-12-23 | ArXiv | 0 | 8 |
visibility_off | Architecture-Aware Learning Curve Extrapolation via Graph Ordinary Differential Equation | Yanna Ding, Zijie Huang, Xiao Shou, Yihang Guo, Yizhou Sun, Jianxi Gao | 2024-12-20 | ArXiv | 0 | 10 |
visibility_off | Towards Ideal Temporal Graph Neural Networks: Evaluations and Conclusions after 10,000 GPU Hours | Yuxin Yang, Hongkuan Zhou, Rajgopal Kannan, Viktor K. Prasanna | 2024-12-28 | ArXiv | 0 | 8 |
Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |