Results 151 to 160 of about 223,849 (180)

Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators

International Conference on Learning Representations
Recently, channel-independent methods have achieved state-of-the-art performance in multivariate time series (MTS) forecasting. Despite reducing overfitting risks, these methods miss potential opportunities in utilizing channel dependence for accurate ...
Lifan Zhao, Yanyan Shen
semanticscholar   +1 more source

Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Neural Information Processing Systems
Large pre-trained models excel in zero/few-shot learning for language and vision tasks but face challenges in multivariate time series (TS) forecasting due to diverse data characteristics.
Vijay Ekambaram, Arindam Jati, Nam H. Nguyen, Pankaj Dayama, Chandra Reddy, Wesley M. Gifford, Jayant Kalagnanam   +6 more
semanticscholar   +1 more source

CATS: Enhancing Multivariate Time Series Forecasting by Constructing Auxiliary Time Series as Exogenous Variables

International Conference on Machine Learning
For Multivariate Time Series Forecasting (MTSF), recent deep learning applications show that univariate models frequently outperform multivariate ones. To address the difficiency in multivariate models, we introduce a method to Construct Auxiliary Time ...
Jiecheng Lu, Xu Han, Yan Sun, Shihao Yang   +3 more
semanticscholar   +1 more source

Dynamic Hypergraph Structure Learning for Multivariate Time Series Forecasting

IEEE Transactions on Big Data
Multivariate time series forecasting plays an important role in many domain applications, such as air pollution forecasting and traffic forecasting. Modeling the complex dependencies among time series is a key challenging task in multivariate time series
Shun-Kai Wang, Yong Zhang, Xuanqi Lin, Yongli Hu, Qingming Huang, Baocai Yin   +5 more
semanticscholar   +1 more source

Saliency-Aware Dual Embedded Attention Network for Multivariate Time-Series Forecasting in Information Technology Operations

IEEE Transactions on Industrial Informatics
In the field of artificial intelligence for information technology operations, operational data are often modeled as aperiodic multivariate time series, which contain rich multidimensional and nonlinear patterns.
Jiajia Li, Feng Tan, Cheng He, Zikai Wang, Haitao Song, Pengwei Hu, Xin Luo   +6 more
semanticscholar   +1 more source

Multivariate Time Series Forecasting: A Review

CVIPPR
Multivariate time series forecasting is a critical task with applications across various domains, including finance, energy demand, and climate modeling.
Kasun Mendis, Manjusri Wickramasinghe, Pasindu Marasinghe   +2 more
semanticscholar   +1 more source

TimePro: Efficient Multivariate Long-term Time Series Forecasting with Variable- and Time-Aware Hyper-state

International Conference on Machine Learning
In long-term time series forecasting, different variables often influence the target variable over distinct time intervals, a challenge known as the multi-delay issue.
Xiaowen Ma, Zhenliang Ni, Shuai Xiao, Xinghao Chen   +3 more
semanticscholar   +1 more source

UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting

Trans. Mach. Learn. Res.
Transformer-based models have emerged as powerful tools for multivariate time series forecasting (MTSF). However, existing Transformer models often fall short of capturing both intricate dependencies across variate and temporal dimensions in MTS data ...
Juncheng Liu, Chenghao Liu, Gerald Woo, Yiwei Wang, Bryan Hooi, Caiming Xiong, Doyen Sahoo   +6 more
semanticscholar   +1 more source

Inconsistent Multivariate Time Series Forecasting

IEEE Transactions on Knowledge and Data Engineering
Traditional statistical time series forecasting models rely on model identification methods to identify the worthiest model variants to investigate; therefore, the model parameters change with the statistical features of rolling windows to reach ...
Li Shen, Yangzhu Wang, Xuyi Fan, Xu Yang, Huaxin Qiu   +4 more
semanticscholar   +1 more source

Hybrid Transformer-CNN architecture for multivariate time series forecasting: Integrating attention mechanisms with convolutional feature extraction

Journal of Intelligence and Information Systems
Abdellah El Zaar, Amine Mansouri, Nabil Benaya, Toufik Bakir, A. Allati   +4 more
semanticscholar   +1 more source