Time-series forecasting
This page was last updated on 2025-03-03 06:06:01 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 | 103 | 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 | 99 | 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 | Neural Information Processing Systems, ArXiv | 27 | 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 | 15 | 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.org, ArXiv | 12 | 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 | 238 | 15 | 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 | 70 | 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 | 137 | 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 | 103 | 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 | 259 | 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 | Neural Information Processing Systems, ArXiv | 7 | 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 | 243 | 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 | 47 | 48 | open_in_new |
visibility_off | AZ-whiteness test: a test for signal uncorrelation on spatio-temporal graphs | Daniele Zambon, C. Alippi | None | DBLP | 7 | 50 | open_in_new |
visibility_off | Graph state-space models | Daniele Zambon, Andrea Cini, L. Livi, C. Alippi | 2023-01-04 | arXiv.org, ArXiv | 5 | 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, DBLP | 8 | 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 | T-Graphormer: Using Transformers for Spatiotemporal Forecasting | Hao Yuan Bai, Xue Liu | 2025-01-22 | ArXiv | 0 | 0 |
visibility_off | TimePFN: Effective Multivariate Time Series Forecasting with Synthetic Data | Ege Onur Taga, M. E. Ildiz, Samet Oymak | 2025-02-22 | ArXiv | 1 | 35 |
visibility_off | Relational Conformal Prediction for Correlated Time Series | Andrea Cini, Alexander Jenkins, D. Mandic, C. Alippi, Filippo Maria Bianchi | 2025-02-13 | ArXiv | 0 | 50 |
visibility_off | Masking the Gaps: An Imputation-Free Approach to Time Series Modeling with Missing Data | A. Neog, Arka Daw, Sepideh Fatemi Khorasgani, A. Karpatne | 2025-02-18 | ArXiv | 0 | 29 |
visibility_off | Using Pre-trained LLMs for Multivariate Time Series Forecasting | Malcolm Wolff, Shenghao Yang, Kari Torkkola, Michael W. Mahoney | 2025-01-10 | ArXiv | 0 | 2 |
visibility_off | Investigating Compositional Reasoning in Time Series Foundation Models | Willa Potosnak, Cristian Challu, Mononito Goswami, Kin G. Olivares, Michał Wiliński, Nina Zukowska, Artur Dubrawski | 2025-02-09 | ArXiv | 0 | 8 |
visibility_off | LAST SToP For Modeling Asynchronous Time Series | Shubham Gupta, Thibaut Durand, Graham Taylor, Lilian W. Bialokozowicz | 2025-02-04 | ArXiv | 0 | 0 |
visibility_off | Vision-Enhanced Time Series Forecasting via Latent Diffusion Models | Weilin Ruan, Siru Zhong, Haomin Wen, Yuxuan Liang | 2025-02-16 | ArXiv | 0 | 6 |
visibility_off | Positional Encoding in Transformer-Based Time Series Models: A Survey | Habib Irani, V. Metsis | 2025-02-17 | ArXiv | 0 | 18 |
visibility_off | SWIFT: Mapping Sub-series with Wavelet Decomposition Improves Time Series Forecasting | Wenxuan Xie, Fanpu Cao | 2025-01-27 | ArXiv | 0 | 0 |
visibility_off | TSKANMixer: Kolmogorov-Arnold Networks with MLP-Mixer Model for Time Series Forecasting | Young-Chae Hong, Bei Xiao, Yangho Chen | 2025-02-25 | ArXiv | 0 | 0 |
visibility_off | Dynamic Trend Fusion Module for Traffic Flow Prediction | Jing Chen, Haocheng Ye, Zhian Ying, Yuntao Sun, Wenqiang Xu | 2025-01-18 | ArXiv | 0 | 7 |
visibility_off | IMTS-Mixer: Mixer-Networks for Irregular Multivariate Time Series Forecasting | Christian Klotergens, Tim Dernedde, Lars Schmidt-Thieme | 2025-02-17 | ArXiv | 0 | 2 |
visibility_off | TimeHF: Billion-Scale Time Series Models Guided by Human Feedback | Yongzhi Qi, Hao Hu, Dazhou Lei, Jianshen Zhang, Zhengxin Shi, Yulin Huang, Zhengyu Chen, Xiaoming Lin, Zuo-Jun Max Shen | 2025-01-27 | ArXiv | 0 | 2 |
visibility_off | Mantis: Lightweight Calibrated Foundation Model for User-Friendly Time Series Classification | Vasilii Feofanov, Songkang Wen, Marius Alonso, Romain Ilbert, Hongbo Guo, Malik Tiomoko, Lujia Pan, Jianfeng Zhang, I. Redko | 2025-02-21 | ArXiv | 0 | 13 |
visibility_off | Mitigating Data Scarcity in Time Series Analysis: A Foundation Model with Series-Symbol Data Generation | Wen-Xia Wang, Kai Wu, Yujian Betterest Li, Dan Wang, Xiaoyu Zhang, Jing Liu | 2025-02-21 | ArXiv | 0 | 2 |
visibility_off | TimeCAP: Learning to Contextualize, Augment, and Predict Time Series Events with Large Language Model Agents | Geon Lee, Wenchao Yu, Kijung Shin, Wei Cheng, Haifeng Chen | 2025-02-17 | ArXiv | 0 | 21 |
visibility_off | TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model | Janghoon Yang | 2025-02-08 | ArXiv | 0 | 0 |
visibility_off | ClimateLLM: Efficient Weather Forecasting via Frequency-Aware Large Language Models | Shixuan Li, Wei Yang, Peiyu Zhang, Xiongye Xiao, De-An Cao, Yuehan Qin, Xiaole Zhang, Yue Zhao, Paul Bogdan | 2025-02-16 | ArXiv | 0 | 5 |
visibility_off | ReFocus: Reinforcing Mid-Frequency and Key-Frequency Modeling for Multivariate Time Series Forecasting | Guoqi Yu, Yaoming Li, Juncheng Wang, Xiaoyu Guo, Angelica I. Avilés-Rivero, Tong Yang, Shujun Wang | 2025-02-24 | ArXiv | 0 | 17 |
visibility_off | AutoCas: Autoregressive Cascade Predictor in Social Networks via Large Language Models | Yuhao Zheng, Chenghua Gong, Rui Sun, Juyuan Zhang, Liming Pan, Linyuan Lv | 2025-02-25 | ArXiv | 0 | 0 |
visibility_off | Efficient Traffic Prediction Through Spatio-Temporal Distillation | Qianru Zhang, Xin Gao, Haixin Wang, S. Yiu, Hongzhi Yin | 2025-01-15 | ArXiv | 1 | 5 |
visibility_off | Harnessing Vision Models for Time Series Analysis: A Survey | Jingchao Ni, Ziming Zhao, ChengAo Shen, Hanghang Tong, Dongjin Song, Wei Cheng, Dongsheng Luo, Haifeng Chen | 2025-02-13 | ArXiv | 0 | 22 |
visibility_off | Spatiotemporal Graph Neural Networks in short term load forecasting: Does adding Graph Structure in Consumption Data Improve Predictions? | Quoc Viet Nguyen, Joaquín Delgado Fernández, Sergio Potenciano Menci | 2025-02-14 | ArXiv | 0 | 5 |
visibility_off | Channel Dependence, Limited Lookback Windows, and the Simplicity of Datasets: How Biased is Time Series Forecasting? | Ibram Abdelmalak, Kiran Madhusudhanan, Jungmin Choi, Maximilian Stubbemann, Lars Schmidt-Thieme | 2025-02-13 | ArXiv | 0 | 3 |
visibility_off | SeisMoLLM: Advancing Seismic Monitoring via Cross-modal Transfer with Pre-trained Large Language Model | Xinghao Wang, Feng Liu, Rui Su, Zhihui Wang, Lei Bai, Wanli Ouyang | 2025-02-27 | ArXiv | 0 | 10 |
visibility_off | TimeDistill: Efficient Long-Term Time Series Forecasting with MLP via Cross-Architecture Distillation | Juntong Ni, Zewen Liu, Shiyu Wang, Ming Jin, Wei Jin | 2025-02-20 | ArXiv | 0 | 3 |
visibility_off | VarDrop: Enhancing Training Efficiency by Reducing Variate Redundancy in Periodic Time Series Forecasting | Junhyeok Kang, Yooju Shin, Jae-Gil Lee | 2025-01-24 | ArXiv | 0 | 8 |
visibility_off | Can Multimodal LLMs Perform Time Series Anomaly Detection? | Xiongxiao Xu, Haoran Wang, Yueqing Liang, , Yue Zhao, Kai Shu | 2025-02-25 | ArXiv | 0 | 7 |
visibility_off | Sliding Window Attention Training for Efficient Large Language Models | Zichuan Fu, Wentao Song, Yejing Wang, Xian Wu, Yefeng Zheng, Yingying Zhang, Derong Xu, Xuetao Wei, Tong Xu, Xiangyu Zhao | 2025-02-26 | ArXiv | 0 | 7 |
visibility_off | An Adaptive Spatio-Temporal Traffic Flow Prediction Using Self-Attention and Multi-Graph Networks | Basma Alsehaimi, Ohoud Alzamzami, Nahed Alowidi, Manar Ali | 2025-01-01 | Sensors (Basel, Switzerland) | 0 | 7 |
visibility_off | Beyond Information Distortion: Imaging Variable-Length Time Series Data for Classification | Hyeonsu Lee, Dongmin Shin | 2025-01-21 | Sensors (Basel, Switzerland) | 0 | 0 |
visibility_off | Mamba-Based Graph Convolutional Networks: Tackling Over-smoothing with Selective State Space | Xingbo He, Yili Wang, Wenqi Fan, Xu Shen, Xin Juan, Rui Miao, Xin Wang | 2025-01-26 | ArXiv | 0 | 4 |
visibility_off | Position: Empowering Time Series Reasoning with Multimodal LLMs | Yaxuan Kong, Yiyuan Yang, Shiyu Wang, Chenghao Liu, Yuxuan Liang, Ming Jin, Stefan Zohren, Dan Pei, Yan Liu, Qingsong Wen | 2025-02-03 | ArXiv | 0 | 7 |
visibility_off | TimeKAN: KAN-based Frequency Decomposition Learning Architecture for Long-term Time Series Forecasting | Songtao Huang, Zhen Zhao, Can Li, Lei Bai | 2025-02-10 | ArXiv | 0 | 0 |
visibility_off | FireCastNet: Earth-as-a-Graph for Seasonal Fire Prediction | Dimitrios Michail, Charalampos Davalas, Lefki-Ioanna Panagiotou, Ioannis Prapas, Spyros Kondylatos, N. Bountos, Ioannis Papoutsis | 2025-02-03 | ArXiv | 0 | 7 |
visibility_off | UniLF: A novel short-term load forecasting model uniformly considering various features from multivariate load data | Shiyang Zhou, Qingyong Zhang, Peng Xiao, Bingrong Xu, Geshuai Luo | 2025-02-04 | Scientific Reports | 0 | 2 |
visibility_off | Progressive Supervision via Label Decomposition: An Long-Term and Large-Scale Wireless Traffic Forecasting Method | Daojun Liang, Haixia Zhang, Dongfeng Yuan | 2025-01-09 | ArXiv | 0 | 29 |
visibility_off | Efficient Time Series Forecasting via Hyper-Complex Models and Frequency Aggregation | Eyal Yakir, Dor Tsur, H. Permuter | 2025-02-27 | ArXiv | 0 | 12 |
visibility_off | A multiscale model for multivariate time series forecasting | V. Naghashi, Mounir Boukadoum, Abdoulaye Baniré Diallo | 2025-01-10 | Scientific Reports | 0 | 13 |
visibility_off | An enhanced Transformer framework with incremental learning for online stock price prediction | Yiming Qian | 2025-01-13 | PLOS ONE | 0 | 0 |
visibility_off | Escaping The Big Data Paradigm in Self-Supervised Representation Learning | Carlos V'elez Garc'ia, Miguel Cazorla, Jorge Pomares | 2025-02-25 | ArXiv | 0 | 0 |
visibility_off | An Adaptive Learning Time Series Forecasting Model Based on Decoder Framework | Jianlong Hao, Qiwei Sun | 2025-01-31 | Mathematics | 0 | 1 |
visibility_off | CENTS: Generating synthetic electricity consumption time series for rare and unseen scenarios | Michael Fuest, Alfredo Cuesta-Infante, K. Veeramachaneni | 2025-01-24 | ArXiv | 0 | 35 |
Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |