Time-series forecasting
This page was last updated on 2025-07-28 06:13:24 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 | 178 | 53 | 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 | 114 | 51 | 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 | 36 | 53 | 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. | 20 | 53 | 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 | 16 | 53 | 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 | 377 | 17 | 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 | 96 | 6 | 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 | International Conference on Machine Learning, ArXiv | 245 | 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 | International Conference on Machine Learning, ArXiv | 206 | 29 | 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 | 422 | 11 | 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 | 36 | 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 | Neural Information Processing Systems, ArXiv | 298 | 51 | 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 | 72 | 51 | open_in_new |
visibility_off | AZ-whiteness test: a test for signal uncorrelation on spatio-temporal graphs | Daniele Zambon, C. Alippi | None | DBLP | 7 | 53 | open_in_new |
visibility_off | Graph state-space models | Daniele Zambon, Andrea Cini, L. Livi, C. Alippi | 2023-01-04 | arXiv.org, ArXiv | 6 | 53 | 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, DBLP | 26 | 51 | 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 | Multi-Scale Finetuning for Encoder-based Time Series Foundation Models | Zhongzheng Qiao, Chenghao Liu, Yiming Zhang, Ming Jin, Quang Pham, Qingsong Wen, P. Suganthan, Xudong Jiang, Savitha Ramasamy | 2025-06-17 | ArXiv | 0 | 114 |
visibility_off | Forecasting Time Series with LLMs via Patch-Based Prompting and Decomposition | Mayank Bumb, Anshul Vemulapalli, Sri Harsha Vardhan Prasad Jella, Anish Gupta, An La, Ryan A. Rossi, Hongjie Chen, Franck Dernoncourt, Nesreen K. Ahmed, Yu Wang | 2025-06-15 | ArXiv | 0 | 11 |
visibility_off | FaCTR: Factorized Channel-Temporal Representation Transformers for Efficient Time Series Forecasting | Yash Vijay, Harini Subramanyan | 2025-06-05 | ArXiv | 0 | 0 |
visibility_off | TimeRecipe: A Time-Series Forecasting Recipe via Benchmarking Module Level Effectiveness | Zhiyuan Zhao, Juntong Ni, Shangqing Xu, Haoxin Liu, Wei Jin, B. A. Prakash | 2025-06-06 | ArXiv | 0 | 10 |
visibility_off | Zero-Shot Time Series Forecasting with Covariates via In-Context Learning | Andreas Auer, Raghul Parthipan, Pedro Mercado, Abdul Fatir Ansari, Lorenzo Stella, Bernie Wang, Michael Bohlke-Schneider, Syama Sundar Rangapuram | 2025-06-03 | ArXiv | 0 | 18 |
visibility_off | TRACE: Grounding Time Series in Context for Multimodal Embedding and Retrieval | Jialin Chen, Ziyu Zhao, G. Nurbek, Aosong Feng, Ali Maatouk, L. Tassiulas, Yifeng Gao, Rex Ying | 2025-06-10 | ArXiv | 0 | 14 |
visibility_off | Binary Cumulative Encoding meets Time Series Forecasting | Andrei Chernov, Vitaliy Pozdnyakov, Ilya Makarov | 2025-05-30 | ArXiv | 0 | 3 |
visibility_off | LETS Forecast: Learning Embedology for Time Series Forecasting | Abrar Majeedi, Viswanatha Reddy Gajjala, Satya Sai Srinath Namburi Gnvv, Nada Magdi Elkordi, Yin Li | 2025-06-06 | ArXiv | 0 | 3 |
visibility_off | Revisiting LLMs as Zero-Shot Time-Series Forecasters: Small Noise Can Break Large Models | Junwoo Park, Hyuck Lee, Dohyun Lee, Daehoon Gwak, Jaegul Choo | 2025-05-31 | ArXiv | 0 | 6 |
visibility_off | ss-Mamba: Semantic-Spline Selective State-Space Model | Zuochen Ye | 2025-06-03 | ArXiv | 0 | 0 |
visibility_off | AMDCnet: attention-gate-based multi-scale decomposition and collaboration network for long-term time series forecasting | Shikang Hou, Song Sun, Tao Yin, Zhibin Zhang, Meng Yan | 2025-05-30 | Frontiers in Artificial Intelligence | 0 | 1 |
visibility_off | Temporal Variational Implicit Neural Representations | Batuhan Koyuncu, Rachael DeVries, Ole Winther, Isabel Valera | 2025-06-02 | ArXiv | 0 | 3 |
visibility_off | A Review of the Long Horizon Forecasting Problem in Time Series Analysis | Hans Krupakar, A. KandappanV | 2025-06-15 | ArXiv | 0 | 3 |
visibility_off | M2WLLM: Multi-Modal Multi-Task Ultra-Short-term Wind Power Prediction Algorithm Based on Large Language Model | Hang Fana, Mingxuan Lib, Zuhan Zhanga, Long Chengc, Yujian Ye, Dunnan Liua | 2025-05-31 | ArXiv | 0 | 0 |
visibility_off | Beyond Attention: Learning Spatio-Temporal Dynamics with Emergent Interpretable Topologies | Sai Vamsi Alisetti, Vikas Kalagi, Sanjukta Krishnagopal | 2025-06-01 | ArXiv | 0 | 10 |
visibility_off | Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting | Chamara Madarasingha, N. Sohrabi, Zahir Tari | 2025-06-03 | ArXiv | 0 | 15 |
visibility_off | Tailored Architectures for Time Series Forecasting: Evaluating Deep Learning Models on Gaussian Process-Generated Data | Victoria Hankemeier, M. Schilling | 2025-06-10 | ArXiv | 0 | 20 |
visibility_off | CoIFNet: A Unified Framework for Multivariate Time Series Forecasting with Missing Values | Kai Tang, Ji Zhang, Hua Meng, Minbo Ma, Qi Xiong, Fengmao Lv, Jie Xu, Tianrui Li | 2025-06-16 | ArXiv | 0 | 7 |
visibility_off | AGGA-MVFLN: Multivariate Time Series Forecasting via Adaptive Generalized Graph Accompanied with Multi-View Learning in Frequency Domain | Jierui Lei, Fangzheng Chen, Haina Tang | 2025-06-30 | Proceedings of the 2025 International Conference on Multimedia Retrieval | 0 | 2 |
visibility_off | A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting | Jiankai Zheng, Liang Xie | 2025-06-01 | ArXiv | 0 | 0 |
visibility_off | SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting | Yitian Zhang, Liheng Ma, Antonios Valkanas, Boris N. Oreshkin, Mark Coates | 2025-06-17 | ArXiv | 0 | 21 |
visibility_off | Unraveling Spatio-Temporal Foundation Models via the Pipeline Lens: A Comprehensive Review | Yuchen Fang, Hao Miao, Yuxuan Liang, Liwei Deng, Yue Cui, Ximu Zeng, Yuyang Xia, Yan Zhao, T. Pedersen, Christian S. Jensen, Xiaofang Zhou, Kai Zheng | 2025-06-02 | ArXiv | 0 | 15 |
visibility_off | MIRA: Medical Time Series Foundation Model for Real-World Health Data | Hao Li, Bowen Deng, Chang Xu, Zhiyuan Feng, Viktor Schlegel, Yu-Hao Huang, Yizheng Sun, Jingyuan Sun, Kailai Yang, Yiyao Yu, Jiang Bian | 2025-06-09 | ArXiv | 0 | 4 |
visibility_off | Towards Robust Real-World Multivariate Time Series Forecasting: A Unified Framework for Dependency, Asynchrony, and Missingness | Jinkwan Jang, Hyungjin Park, Jinmyeong Choi, Taesup Kim | 2025-06-10 | ArXiv | 0 | 0 |
visibility_off | Multivariate Time-series Transformer Embeddings for Light Curves | Gabriel Chiong, I. Becker, P. Protopapas | 2025-06-13 | ArXiv | 0 | 35 |
visibility_off | Wavelet-based Disentangled Adaptive Normalization for Non-stationary Times Series Forecasting | Junpeng Lin, Tian Lan, Bo Zhang, Ke Lin, Dandan Miao, Huiru He, Jiantao Ye, Chen Zhang, Yan-fu Li | 2025-06-06 | ArXiv | 0 | 1 |
visibility_off | STFDSGCN: Spatio-Temporal Fusion Graph Neural Network Based on Dynamic Sparse Graph Convolution GRU for Traffic Flow Forecast | Jiahao Chang, Jiali Yin, Yanrong Hao, Chengxin Gao | 2025-05-30 | Sensors (Basel, Switzerland) | 0 | 2 |
visibility_off | Regularized Adaptive Graph Learning for Large-Scale Traffic Forecasting | Kaiqi Wu, Weiyang Kong, Sen Zhang, Yubao Liu, Zitong Chen | 2025-06-08 | ArXiv | 0 | 7 |
visibility_off | AutoHFormer: Efficient Hierarchical Autoregressive Transformer for Time Series Prediction | Qianru Zhang, Honggang Wen, Ming Li, Dong Huang, S. Yiu, Christian S. Jensen, Pietro Liò | 2025-06-19 | ArXiv | 0 | 6 |
visibility_off | Multivariate Long-term Time Series Forecasting with Fourier Neural Filter | Chenheng Xu, Dan Wu, Yixin Zhu, Yingqi Wu | 2025-06-10 | ArXiv | 0 | 1 |
visibility_off | Over-squashing in Spatiotemporal Graph Neural Networks | Ivan Marisca, Jacob Bamberger, C. Alippi, Michael M. Bronstein | 2025-06-18 | ArXiv | 0 | 53 |
visibility_off | XicorAttention: Time Series Transformer Using Attention with Nonlinear Correlation | Daichi Kimura, Tomonori Izumitani, Hisashi Kashima | 2025-06-03 | ArXiv | 0 | 6 |
visibility_off | Forecast-Then-Optimize Deep Learning Methods | Jinhang Jiang, Nan Wu, Ben Liu, Mei Feng, Xin Ji, Karthik Srinivasan | 2025-06-16 | ArXiv | 0 | 5 |
visibility_off | A Survey of Retentive Network | Haiqi Yang, Zhiyuan Li, Yi Chang, Yuan Wu | 2025-06-07 | ArXiv | 0 | 4 |
visibility_off | DisMS-TS: Eliminating Redundant Multi-Scale Features for Time Series Classification | Zhipeng Liu, Peibo Duan, Binwu Wang, Xuan Tang, Qi Chu, Changsheng Zhang, Yongsheng Huang, Bin Zhang | 2025-07-07 | ArXiv | 0 | 2 |
visibility_off | Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision | Jiahui Zhou, Dan Li, Lin Li, Zhuomin Chen, Shunyu Wu, Haozheng Ye, Jian Lou, C. Spanos | 2025-06-01 | ArXiv | 0 | 54 |
visibility_off | Harnessing Vision-Language Models for Time Series Anomaly Detection | Zelin He, Sarah Alnegheimish, Matthew Reimherr | 2025-06-07 | ArXiv | 0 | 7 |
visibility_off | Spatio-temporal transformer and graph convolutional networks based traffic flow prediction | Jin Zhang, Yimin Yang, Xiaoheng Wu, Sen Li | 2025-07-07 | Scientific Reports | 0 | 0 |
visibility_off | KARMA: A Multilevel Decomposition Hybrid Mamba Framework for Multivariate Long-Term Time Series Forecasting | Hang Ye, Gaoxiang Duan, Haoran Zeng, Yangxin Zhu, Lingxue Meng, Xiaoying Zheng, Yongxin Zhu | 2025-06-10 | ArXiv, DBLP | 0 | 5 |
visibility_off | Time-Series Forecasting Method Based on Hierarchical Spatio-Temporal Attention Mechanism | Zhiguo Xiao, Junli Liu, Xinyao Cao, Ke Wang, Dongni Li, Qian Liu | 2025-06-26 | Sensors (Basel, Switzerland) | 0 | 1 |
visibility_off | Filling the Missings: Spatiotemporal Data Imputation by Conditional Diffusion | Wenying He, Jieling Huang, Junhua Gu, Ji Zhang, Yude Bai | 2025-06-08 | ArXiv | 0 | 2 |
visibility_off | Delayformer: spatiotemporal transformation for predicting high-dimensional dynamics | Zijian Wang, Peng Tao, Luonan Chen | 2025-06-13 | ArXiv | 0 | 5 |
visibility_off | TFKAN: Time-Frequency KAN for Long-Term Time Series Forecasting | Xiaoyan Kui, Canwei Liu, Qinsong Li, Zhipeng Hu, Yangyang Shi, Weixin Si, Beiji Zou | 2025-06-15 | ArXiv | 0 | 10 |
visibility_off | Gaussian Process Latent Variable Modeling for Few-Shot Time Series Forecasting | Yunyao Cheng, Chenjuan Guo, Kaixuan Chen, Kai Zhao, Bin Yang, Jiandong Xie, Christian S. Jensen, Feiteng Huang, Kai Zheng | 2025-08-01 | IEEE Transactions on Knowledge and Data Engineering | 0 | 32 |
Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |