111 citations · 310 across the 38 of their papers we have counts for
7 papers · 1 filter
RGP: Neural Network Pruning through Its Regular Graph Structure
Zhuangzhi Chen, Jingyang Xiang, Yao Lu +2
Lightweight model design has become an important direction in the application of deep learning technology, pruning is an effective mean to achieve a large reduction in model parame…
Understanding the Dynamics of DNNs Using Graph Modularity
Yao Lu, Wen Yang, Yunzhe Zhang +5
There are good arguments to support the claim that deep neural networks (DNNs) capture better feature representations than the previous hand-crafted feature engineering, which lead…
Graph-Based Similarity of Neural Network Representations
Zuohui Chen, Yao Lu, Jinxuan Hu +4
Understanding the black-box representations in Deep Neural Networks (DNN) is an essential problem in deep learning. In this work, we propose Graph-Based Similarity (GBS) to measure…
Deep Transfer Clustering of Radio Signals
Qi Xuan, Xiaohui Li, Zhuangzhi Chen +3
Modulation recognition is an important task in radio signal processing. Most of the current researches focus on supervised learning. However, in many real scenarios, it is difficul…
GGT: Graph-Guided Testing for Adversarial Sample Detection of Deep Neural Network
Zuohui Chen, Renxuan Wang, Jingyang Xiang +5
Deep Neural Networks (DNN) are known to be vulnerable to adversarial samples, the detection of which is crucial for the wide application of these DNN models. Recently, a number of…
Adaptive Visibility Graph Neural Network and its Application in Modulation Classification
Qi Xuan, Kunfeng Qiu, Jinchao Zhou +4
Our digital world is full of time series and graphs which capture the various aspects of many complex systems. Traditionally, there are respective methods in processing these two d…
CLPVG: Circular limited penetrable visibility graph as a new network model for time series
Qi Xuan, Jinchao Zhou, Kunfeng Qiu +3
Visibility Graph (VG) transforms time series into graphs, facilitating signal processing by advanced graph data mining algorithms. In this paper, based on the classic Limited Penet…