Learning graph edit distance by graph neural networks-Reference-Cited by-同舟云学术

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Learning graph edit distance by graph neural networks

Published:2021-12 Issue: Volume:120 Page:108132
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Riba Pau,Fischer Andreas,Lladós Josep,Fornés Alicia

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference67 articles.

1. Graph R-CNN for scene graph generation;Yang,2018

2. Neural message passing for quantum chemistry;Gilmer,2017

3. Mesh R-CNN;Gkioxari,2019

4. Learning binary code for fast nearest subspace search;Zhou;Pattern Recognit.,2020

5. Graph characteristics from the heat kernel trace;Xiao;Pattern Recognit.,2009

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

2. Transferable graph auto-encoders for cross-network node classification;Pattern Recognition;2024-06

3. Research of trajectory similarity metric based on improved graph edit distance and ITS application;Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023);2024-05-22

5. A Wasserstein Graph Distance Based on Distributions of Probabilistic Node Embeddings;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

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