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Network Robustness Prediction: Influence of Training Data Distributions
Yang Lou
*
, Chengpei Wu, Junli Li
*
, Lin Wang, Guanrong Chen
*
此作品的通信作者
資訊工程學系
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6
引文 斯高帕斯（Scopus）
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Keyphrases
Feature Representation
100%
Network Robustness
100%
Learned Features
100%
Training Data Distribution
100%
Convolutional Neural Network
66%
Training Data
33%
Performance Prediction
33%
Input Size
33%
Unseen
16%
Malicious Attacks
16%
Network Size
16%
Uniform Distribution
16%
General Learning
16%
Neural Network Prediction
16%
Removal Attack
16%
Industrial Networks
16%
Robustness Evaluation
16%
Node Removal
16%
Edge Removal
16%
Extension Ability
16%
Natural Network
16%
Attack Simulation
16%
Computer Science
Convolutional Neural Network
100%
Training Data
100%
Data Distribution
100%
Representation Learning
66%
Prediction Performance
22%
Experimental Result
11%
Malicious Attack
11%
Uniform Distribution
11%
Optimal Setting
11%
Generalizability
11%
Industrial Network
11%
Engineering
Convolutional Neural Network
100%
Gaussians
22%
Prediction Performance
22%
Experimental Result
11%
Nodes
11%
Optimal Setting
11%
Neural Network Input
11%
Industrial Network
11%
Chemical Engineering
Neural Network
100%