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Graph-patchformer: Patch interaction transformer with adaptive graph learning for multivariate time series forecasting

delete2025-09-25
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PRE
AI
C
Chunyi Hou
Y
Yongchuan Yu
J
Jinquan Ji
S
Siyao Zhang
X
Xumeng Shen
J
Jianzhuo Yan
DOI:10.1016/j.neunet.2025.108140delete
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Abstract

Abstract

En 中文
• Proposing structural encodings to improve the predictor’s performance. • Designing Patch Interaction Block (NIB) to promote broad interactions among patches. • Experiments on twelve benchmarks demonstrate the effectiveness of the proposed method.

Journal

Neural Networks cover
Neural Networks
IF:
6.3
Papers:
7.8K
Citations:
3.0W

Organization

D
Dongbei University of Finance and Economics
Scholars:
330
Papers: 244
Citations: 2.2K
B
Beijing University of Technology
Scholars:
2.8W
Papers: 2.1W
Citations: 2.7W