132 citations · 683 across the 107 of their papers we have counts for
19 papers · 1 filter
BlockGC: A Joint Learning Framework for Account Identity Inference on Blockchain with Graph Contrast
Jiajun Zhou, Chenkai Hu, Shenbo Gong +3
Blockchain technology has the characteristics of decentralization, traceability and tamper proof, which creates a reliable decentralized transaction mode, further accelerating the…
Inductive Subgraph Embedding for Link Prediction
Chunyu Miao, Chenxuan Xie, Jiajun Zhou +3
Graph representation learning (GRL) has emerged as a powerful technique for solving graph analytics tasks. It can effectively convert discrete graph data into a low-dimensional spa…
Null Model-Based Data Augmentation for Graph Classification
Qi Xuan, Zeyu Wang, Jinhuan Wang +3
In network science, the null model is typically used to generate a series of graphs based on randomization as a term of comparison to verify whether a network in question displays…
COREATTACK: Breaking Up the Core Structure of Graphs
Bo Zhou, Yuqian Lv, Jinhuan Wang +2
The concept of k-core in complex networks plays a key role in many applications, e.g., understanding the global structure, or identifying central/critical nodes, of a network. A ma…
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…
The Robustness of Graph k-shell Structure under Adversarial Attacks
B. Zhou, Y. Q. Lv, Y. C. Mao +3
The k-shell decomposition plays an important role in unveiling the structural properties of a network, i.e., it is widely adopted to find the densest part of a network across a bro…
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…
DeepInsight: Interpretability Assisting Detection of Adversarial Samples on Graphs
Junhao Zhu, Yalu Shan, Jinhuan Wang +3
With the rapid development of artificial intelligence, a number of machine learning algorithms, such as graph neural networks have been proposed to facilitate network analysis or g…
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…
TSGN: Transaction Subgraph Networks for Identifying Ethereum Phishing Accounts
Jinhuan Wang, Pengtao Chen, Shanqing Yu +1
Blockchain technology and, in particular, blockchain-based transaction offers us information that has never been seen before in the financial world. In contrast to fiat currencies,…
Ponzi Scheme Detection in EthereumTransaction Network
Shanqing Yu, Jie Jin, Yunyi Xie +2
With the rapid growth of blockchain, an increasing number of users have been attracted and many implementations have been refreshed in different fields. Especially in the cryptocur…
Identity Inference on Blockchain using Graph Neural Network
Jie Shen, Jiajun Zhou, Yunyi Xie +2
The anonymity of blockchain has accelerated the growth of illegal activities and criminal behaviors on cryptocurrency platforms. Although decentralization is one of the typical cha…
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…
MITNet: GAN Enhanced Magnetic Induction Tomography Based on Complex CNN
Zuohui Chen, Qing Yuan, Xujie Song +5
Magnetic induction tomography (MIT) is an efficient solution for long-term brain disease monitoring, which focuses on reconstructing bio-impedance distribution inside the human bra…
Sampling Subgraph Network with Application to Graph Classification
Jinhuan Wang, Pengtao Chen, Bin Ma +4
Graphs are naturally used to describe the structures of various real-world systems in biology, society, computer science etc., where subgraphs or motifs as basic blocks play an imp…
HVAQ: A High-Resolution Vision-Based Air Quality Dataset
Zuohui Chen, Tony Zhang, Zhuangzhi Chen +3
Air pollutants, such as particulate matter, negatively impact human health. Most existing pollution monitoring techniques use stationary sensors, which are typically sparsely deplo…