Adversarial Attack and Training for Graph Convolutional Networks Using Focal Loss-Projected Momentum-Reference-Cited by-同舟云学术

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Adversarial Attack and Training for Graph Convolutional Networks Using Focal Loss-Projected Momentum

Published:2024-04-13 Issue: Volume:absI1609.02907 Page:1-5
ISSN:
Container-title:2024 IEEE 3rd International Conference on Computing and Machine Intelligence (ICMI)
language:
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Author:

Aburidi Mohammed¹,Marcia Roummel F.¹

Affiliation:

1. University of California Merced,Department of Applied Mathematics,Merced,USA

Funder

NSF

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10585267/10585616/10586025.pdf?arnumber=10586025

Reference28 articles.

1. Semi-Supervised Classification with Graph Convolutional Networks;Kipf;CoRR,2016

2. Graph Attention Networks;Velickovic;arXiv [stat.ML],2018

3. How Powerful are Graph Neural Networks?;Xu;CoRR,2018

4. Wasserstein Distance-Based Graph Kernel for Enhancing Drug Safety and Efficacy Prediction *

5. Optimal Transport-Based Graph Kernels for Drug Property Prediction;Aburidi;Scientific reports,2024

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