This page was last updated on 2024-09-16 06:05:59 UTC
Recommendations for the article Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series
Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index |
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visibility_off | VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters | Mouxiang Chen, Lefei Shen, Zhuo Li, Xiaoyun Joy Wang, Jianling Sun, Chenghao Liu | 2024-08-30 | ArXiv | 0 | 3 |
visibility_off | Only the Curve Shape Matters: Training Foundation Models for Zero-Shot Multivariate Time Series Forecasting through Next Curve Shape Prediction | Cheng Feng, Long Huang, Denis Krompass | 2024-02-12 | ArXiv | 3 | 14 |
visibility_off | Generative Pre-Trained Diffusion Paradigm for Zero-Shot Time Series Forecasting | Jiarui Yang, Tao Dai, Naiqi Li, Junxi Wu, Peiyuan Liu, Jinmin Li, Jigang Bao, Haigang Zhang, Shu-Tao Xia | 2024-06-04 | ArXiv | 0 | 4 |
visibility_off | Chronos: Learning the Language of Time Series | Abdul Fatir Ansari, Lorenzo Stella, Caner Turkmen, Xiyuan Zhang, Pedro Mercado, Huibin Shen, Oleksandr Shchur, Syama Sundar Rangapuram, Sebastian Pineda Arango, Shubham Kapoor, Jasper Zschiegner, Danielle C. Maddix, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Yuyang Wang | 2024-03-12 | ArXiv | 28 | 18 |
visibility_off | Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting | Kashif Rasul, Arjun Ashok, Andrew Robert Williams, Arian Khorasani, George Adamopoulos, Rishika Bhagwatkar, Marin Bilovs, Hena Ghonia, N. Hassen, Anderson Schneider, Sahil Garg, Alexandre Drouin, Nicolas Chapados, Yuriy Nevmyvaka, I. Rish | 2023-10-12 | ArXiv | 16 | 40 |
visibility_off | A Survey of Time Series Foundation Models: Generalizing Time Series Representation with Large Language Model | Jiexia Ye, Weiqi Zhang, Ke Yi, Yongzi Yu, Ziyue Li, Jia Li, F. Tsung | 2024-05-03 | ArXiv | 4 | 47 |
visibility_off | Multi-Patch Prediction: Adapting LLMs for Time Series Representation Learning | Yuxuan Bian, Xu Ju, Jiangtong Li, Zhijian Xu, Dawei Cheng, Qiang Xu | 2024-02-07 | ArXiv | 6 | 5 |
visibility_off | Pushing the Limits of Pre-training for Time Series Forecasting in the CloudOps Domain | Gerald Woo, Chenghao Liu, Akshat Kumar, Doyen Sahoo | 2023-10-08 | ArXiv | 7 | 22 |
visibility_off | One Fits All: Universal Time Series Analysis by Pretrained LM and Specially Designed Adaptors | Tian Zhou, Peisong Niu, Xue Wang, Liang Sun, Rong Jin | 2023-11-24 | ArXiv | 4 | 7 |
Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |