Jan 22, 2022 · To tackle such issues, we propose a novel Transformer-based model for multivariate time series forecasting, called the spatial–temporal ...
Jan 22, 2022 · To tackle such issues, we propose a novel Transformer-based model for multivariate time series forecasting, called the spatial-temporal ...
Spacetimeformer is a Transformer that learns temporal patterns like a time series model and spatial patterns like a Graph Neural Network. Below we give a ...
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A novel Transformer-based model for multivariate time series forecasting, called the spatial–temporal convolutional Transformer network (STCTN), ...
Multi-view spatial-temporal graph convolutional networks with domain ... Short-term wind speed forecasting based on spatial-temporal graph transformer networks ( ...
Feb 19, 2024 · The spatial linear transformer effectively reduces the complexity of data calculation and storage while capturing spatial dependence, and the ...
In this paper, we propose the Adaptive Fused Spatial-Temporal Graph Convolutional Network (AFSTGCN). First, to address the problem of the unknown spatial- ...
This paper proposes a general-purpose multivariate forecaster with the long-term prediction ability of a time series model and the dynamic spatial modeling of a ...
Mar 4, 2024 · Traffic forecasting is a complex multivariate time-series regression task of paramount importance for traffic management and planning.
Mar 6, 2024 · The proposed model has a structure that extracts temporal features of input data through a CNN and interprets the correlation between variables ...
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