research
∙
06/23/2023
PathMLP: Smooth Path Towards High-order Homophily
Real-world graphs exhibit increasing heterophily, where nodes no longer ...
share
research
∙
06/06/2023
Subgraph Networks Based Contrastive Learning
Graph contrastive learning (GCL), as a self-supervised learning method, ...
research
∙
08/27/2022
TSGN: Transaction Subgraph Networks Assisting Phishing Detection in Ethereum
Due to the decentralized and public nature of the Blockchain ecosystem, ...
research
∙
04/05/2022
Mixing Signals: Data Augmentation Approach for Deep Learning Based Modulation Recognition
With the rapid development of deep learning, automatic modulation recogn...
research
∙
11/24/2021
Graph Modularity: Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Neural Networks
There are good arguments to support the claim that feature representatio...
research
∙
11/22/2021
Graph-Based Similarity of Neural Network Representations
Understanding the black-box representations in Deep Neural Networks (DNN...
research
∙
07/09/2021
GGT: Graph-Guided Testing for Adversarial Sample Detection of Deep Neural Network
Deep Neural Networks (DNN) are known to be vulnerable to adversarial sam...
research
∙
06/16/2021
Adaptive Visibility Graph Neural Network and its Application in Modulation Classification
Our digital world is full of time series and graphs which capture the va...
research
∙
09/13/2019
Spectrum Sensing Based on Deep Learning Classification for Cognitive Radios
Spectrum sensing is a key technology for cognitive radios. We present sp...
research
∙
07/21/2019
Open DNN Box by Power Side-Channel Attack
Deep neural networks are becoming popular and important assets of many A...
research
∙
04/20/2019