Time-series forecasting
This page was last updated on 2025-06-23 11:22:53 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 | 167 | 52 | 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 | 113 | 50 | 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 | 52 | 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 | 19 | 52 | 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 | 52 | 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 | 368 | 16 | 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, arXiv.org | 94 | 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 | International Conference on Machine Learning, ArXiv | 241 | 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 | 202 | 26 | 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 | 414 | 10 | 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 | 34 | 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 | 288 | 50 | 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 | 68 | 50 | open_in_new |
visibility_off | AZ-whiteness test: a test for signal uncorrelation on spatio-temporal graphs | Daniele Zambon, C. Alippi | None | DBLP | 7 | 52 | open_in_new |
visibility_off | Graph state-space models | Daniele Zambon, Andrea Cini, L. Livi, C. Alippi | 2023-01-04 | ArXiv, arXiv.org | 6 | 52 | 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 | DBLP, ArXiv | 25 | 50 | 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 | DELPHYNE: A Pre-Trained Model for General and Financial Time Series | Xueying Ding, Aakriti Mittal, Achintya Gopal | 2025-05-12 | ArXiv | 0 | 1 |
visibility_off | Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations | Yu-Hsiang Lan, E. Oermann | 2025-05-01 | ArXiv | 0 | 3 |
visibility_off | Time Tracker: Mixture-of-Experts-Enhanced Foundation Time Series Forecasting Model with Decoupled Training Pipelines | Xiaohou Shi, Ke Li, Aobo Liang, Y. Sun | 2025-05-21 | ArXiv | 0 | 3 |
visibility_off | Output Scaling: YingLong-Delayed Chain of Thought in a Large Pretrained Time Series Forecasting Model | Xue Wang, Tian Zhou, Jinyang Gao, Bolin Ding, Jingren Zhou | 2025-05-20 | ArXiv | 0 | 8 |
visibility_off | TSPulse: Dual Space Tiny Pre-Trained Models for Rapid Time-Series Analysis | Vijay Ekambaram, Subodh Kumar, Arindam Jati, Sumanta Mukherjee, Tomoya Sakai, Pankaj Dayama, Wesley M. Gifford, Jayant Kalagnanam | 2025-05-19 | ArXiv | 0 | 4 |
visibility_off | TiRex: Zero-Shot Forecasting Across Long and Short Horizons with Enhanced In-Context Learning | Andreas Auer, Patrick Podest, Daniel Klotz, Sebastian Bock, G. Klambauer, Sepp Hochreiter | 2025-05-29 | ArXiv | 0 | 55 |
visibility_off | Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge Distillation | Chenxi Liu, Hao Miao, Qianxiong Xu, Shaowen Zhou, Cheng Long, Yan Zhao, Ziyue Li, Rui Zhao | 2025-05-04 | ArXiv | 7 | 9 |
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 | 113 |
visibility_off | Logo-LLM: Local and Global Modeling with Large Language Models for Time Series Forecasting | Wenjie Ou, Zhishuo Zhao, Dongyue Guo, Yi Lin | 2025-05-16 | ArXiv | 0 | 11 |
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 | 10 |
visibility_off | Time to Embed: Unlocking Foundation Models for Time Series with Channel Descriptions | Utsav Dutta, S. Pakazad, Henrik Ohlsson | 2025-05-20 | ArXiv | 0 | 11 |
visibility_off | Should We Reconsider RNNs for Time-Series Forecasting? | V. Naghashi, Mounir Boukadoum, A. Diallo | 2025-04-25 | AI | 0 | 13 |
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 | IMTS is Worth Time $\times$ Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series Prediction | Zhangyi Hu, Jiemin Wu, Hua Xu, Mingqian Liao, Ninghui Feng, Bo Gao, Songning Lai, Yutao Yue | 2025-05-28 | ArXiv | 0 | 4 |
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 | 8 |
visibility_off | HyperIMTS: Hypergraph Neural Network for Irregular Multivariate Time Series Forecasting | Boyuan Li, Yicheng Luo, Zhen Liu, Junhao Zheng, Jianming Lv, Qianli Ma | 2025-05-23 | ArXiv | 0 | 8 |
visibility_off | Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting | Yueyang Yao, Jiajun Li, Xingyuan Dai, Mengmeng Zhang, Xiaoyan Gong, Fei-Yue Wang, Yisheng Lv | 2025-05-16 | ArXiv | 0 | 4 |
visibility_off | STRGCN: Capturing Asynchronous Spatio-Temporal Dependencies for Irregular Multivariate Time Series Forecasting | Yulong Wang, Xiaofeng Hu, Xiaojian Cui, Kai Wang | 2025-05-07 | ArXiv | 0 | 0 |
visibility_off | Enhancing LLMs for Time Series Forecasting via Structure-Guided Cross-Modal Alignment | Siming Sun, Kai Zhang, Xuejun Jiang, Wenchao Meng, Qinmin Yang | 2025-05-19 | ArXiv | 0 | 21 |
visibility_off | Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting | Licheng Pan, Zhichao Chen, Haoxuan Li, Guangyi Liu, Zhijiang Xu, Zhaoran Liu, Hao Wang, Ying Wei | 2025-05-23 | ArXiv | 0 | 7 |
visibility_off | Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting | Chengsen Wang, Qi Qi, Jingyu Wang, Haifeng Sun, Zirui Zhuang, Jianxin Liao | 2025-05-01 | ArXiv | 0 | 28 |
visibility_off | TSRM: A Lightweight Temporal Feature Encoding Architecture for Time Series Forecasting and Imputation | Robert Leppich, Michael Stenger, Daniel Grillmeyer, Vanessa Borst, Samuel Kounev | 2025-04-26 | ArXiv | 0 | 9 |
visibility_off | Enhancing Channel-Independent Time Series Forecasting via Cross-Variate Patch Embedding | Donghwa Shin, Edwin Zhang | 2025-05-19 | ArXiv | 0 | 0 |
visibility_off | Binary Cumulative Encoding meets Time Series Forecasting | Andrei Chernov, Vitaliy Pozdnyakov, Ilya Makarov | 2025-05-30 | ArXiv | 0 | 3 |
visibility_off | CASA: CNN Autoencoder-based Score Attention for Efficient Multivariate Long-term Time-series Forecasting | Minhyuk Lee, Hyekyung Yoon, Myungjoo Kang | 2025-05-04 | ArXiv | 0 | 2 |
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 | 2 |
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 | 5 |
visibility_off | Are Data Embeddings effective in time series forecasting? | Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan | 2025-05-27 | ArXiv | 0 | 9 |
visibility_off | ss-Mamba: Semantic-Spline Selective State-Space Model | Zuochen Ye | 2025-06-03 | ArXiv | 0 | 0 |
visibility_off | Towards Cross-Modality Modeling for Time Series Analytics: A Survey in the LLM Era | Chenxi Liu, Shaowen Zhou, Qianxiong Xu, Hao Miao, Cheng Long, Ziyue Li, Rui Zhao | 2025-05-05 | ArXiv | 2 | 9 |
visibility_off | Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting | Zhining Liu, Ze Yang, Xiao Lin, Ruizhong Qiu, Tianxin Wei, Yada Zhu, Hendrik Hamann, Jingrui He, Hanghang Tong | 2025-05-24 | ArXiv | 0 | 7 |
visibility_off | Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks | Ali Forootani, Mohammad Khosravi | 2025-05-26 | ArXiv | 0 | 6 |
visibility_off | Leveraging Long-Term Multivariate History Representation for Time Series Forecasting | Huiliang Zhang, Di Wu, Arnaud Zinflou, Stephane Dellacherie, M. Dione, Benoit Boulet | 2025-05-20 | IEEE Transactions on Artificial Intelligence | 0 | 8 |
visibility_off | SPAT: Sensitivity-based Multihead-attention Pruning on Time Series Forecasting Models | Suhan Guo, Jiahong Deng, Mengjun Yi, Furao Shen, Jian Zhao | 2025-05-13 | ArXiv | 0 | 4 |
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 Query Network for Efficient Multivariate Time Series Forecasting | Shengsheng Lin, Haojun Chen, Haijie Wu, Chunyun Qiu, Weiwei Lin | 2025-05-19 | ArXiv | 0 | 4 |
visibility_off | This Time is Different: An Observability Perspective on Time Series Foundation Models | Ben Cohen, E. Khwaja, Youssef Doubli, Salahidine Lemaachi, Chris Lettieri, Charles Masson, Hugo Miccinilli, Elise Ram'e, Qiqi Ren, Afshin Rostamizadeh, Jean Ogier du Terrail, A. Toon, Kan Wang, Stephan Xie, David Asker, Ameet Talwalkar, Othmane Abou-Amal | 2025-05-20 | ArXiv | 0 | 50 |
visibility_off | CrossLinear: Plug-and-Play Cross-Correlation Embedding for Time Series Forecasting with Exogenous Variables | Pengfei Zhou, Yunlong Liu, Junli Liang, Qi Song, Xiangyang Li | 2025-05-29 | ArXiv | 0 | 1 |
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 | Rethinking Irregular Time Series Forecasting: A Simple yet Effective Baseline | Xvyuan Liu, Xiangfei Qiu, Xingjian Wu, Zhengyu Li, Chenjuan Guo, Jilin Hu, Bin Yang | 2025-05-16 | ArXiv | 0 | 30 |
visibility_off | Time Series Generation Under Data Scarcity: A Unified Generative Modeling Approach | T. Gonen, Itai Pemper, Ilan Naiman, Nimrod Berman, Omri Azencot | 2025-05-26 | ArXiv | 0 | 19 |
visibility_off | TimePro: Efficient Multivariate Long-term Time Series Forecasting with Variable- and Time-Aware Hyper-state | Xiaowen Ma, Zhenliang Ni, Shuai Xiao, Xinghao Chen | 2025-05-27 | ArXiv | 0 | 2 |
visibility_off | Dual-Forecaster: A Multimodal Time Series Model Integrating Descriptive and Predictive Texts | Wenfa Wu, Guanyu Zhang, Zheng Tan, Yi Wang, Hongsheng Qi | 2025-05-02 | ArXiv | 2 | 1 |
visibility_off | Forging Time Series with Language: A Large Language Model Approach to Synthetic Data Generation | Cécile Rousseau, Tobia Boschi, Giandomenico Cornacchia, Dhaval Salwala, Alessandra Pascale, Juan Bernabe Moreno | 2025-05-21 | ArXiv | 0 | 5 |
visibility_off | Beyond Attention: Learning Spatio-Temporal Dynamics with Emergent Interpretable Topologies | Sai Vamsi Alisetti, Vikas Kalagi, Sanjukta Krishnagopal | 2025-06-01 | ArXiv | 0 | 9 |
visibility_off | Retrieval Augmented Time Series Forecasting | Sungwon Han, Seungeon Lee, Meeyoung Cha, Sercan Ö. Arik, Jinsung Yoon | 2025-05-07 | ArXiv | 0 | 35 |
visibility_off | Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting | Mert Onur Cakiroglu, Idil Bilge Altun, Hasan Kurban, Elham Buxton, Mehmet M. Dalkilic | 2025-05-28 | ArXiv | 0 | 1 |
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 |
Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |