Meta Structure Search for Link Weight Prediction in Heterogeneous Graphs-Reference-Cited by-同舟云学术

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Meta Structure Search for Link Weight Prediction in Heterogeneous Graphs

Published:2024-04-14 Issue: Volume:2003 Page:5195-5199
ISSN:
Container-title:ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Zhang Xiaoou¹,Gao Yang²,Liu Yang³,Zhu Yujia¹,Zhang Peng⁴,Zhou Chuan³,Liu Qingyun¹,Chen Hongyang⁵

Affiliation:

1. Institute of Information Engineering,Chinese Academy of Sciences

2. Zhejiang University,College of Computer Science and Technology

3. Academy of Mathematics and Systems Science,Chinese Academy of Sciences

4. Guangzhou University,Cyberspace Institute of Advanced Technology

5. Research Center for Graph Computing,Zhejiang Lab

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10445798/10445803/10448349.pdf?arnumber=10448349

Reference31 articles.

1. Statistical relational learning for link prediction;Popescul

2. CurvDrop: A Ricci Curvature Based Approach to Prevent Graph Neural Networks from Over-Smoothing and Over-Squashing

3. A Hybrid Deep Learning Model With Attention-Based Conv-LSTM Networks for Short-Term Traffic Flow Prediction

4. From Discrimination to Generation: Knowledge Graph Completion with Generative Transformer

5. Link Weight Prediction Using Supervised Learning Methods and Its Application to Yelp Layered Network

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