Class-based attack on graph convolution network
Prevalent use of graph structure data for classification tasks has brought attention to the robustness of graph convolutional networks. Recent study has been shown that graph convolutional networks are vulnerable to adversary attacks, causing a severe threat to real world application. In this report...
Saved in:
Main Author: | He, HeFei |
---|---|
Other Authors: | Anupam Chattopadhyay |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/156472 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Semi supervised learning with graph convolutional networks
by: Ong, Jia Rui
Published: (2019) -
Graph convolutional neural networks for text categorization
by: Lakhotia, Suyash
Published: (2018) -
Graph convolutional neural networks for the travelling salesman problem
by: Joshi, Chaitanya Krishna
Published: (2019) -
Universal adversarial attacks on graph neural networks
by: Liao, Chang
Published: (2021) -
Natural language translation with graph convolutional neural network
by: Zhu, Yimin
Published: (2018)