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20212024
most citedNeighborhood Homophily-based Graph Convolutional Network

13 citations · 29 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CR2024★ 1 cited

Facilitating Feature and Topology Lightweighting: An Ethereum Transaction Graph Compression Method for Malicious Account Detection

Jiajun Zhou, Xuanze Chen, Shengbo Gong +4

Ethereum has become one of the primary global platforms for cryptocurrency, playing an important role in promoting the diversification of the financial ecosystem. However, the rela…

cs.SI2023★ 1 cited

Multi-triplet Feature Augmentation for Ponzi Scheme Detection in Ethereum

Chengxiang Jin, Jiajun Zhou, Shengbo Gong +2

Blockchain technology revolutionizes the Internet, but also poses increasing risks, particularly in cryptocurrency finance. On the Ethereum platform, Ponzi schemes, phishing scams,…

cs.LG2023★ 1 cited

PathMLP: Smooth Path Towards High-order Homophily

Jiajun Zhou, Chenxuan Xie, Shengbo Gong +4

Real-world graphs exhibit increasing heterophily, where nodes no longer tend to be connected to nodes with the same label, challenging the homophily assumption of classical graph n…

cs.LG2023★ 6 cited

Clarify Confused Nodes via Separated Learning

Jiajun Zhou, Shengbo Gong, Xuanze Chen +4

Graph neural networks (GNNs) have achieved remarkable advances in graph-oriented tasks. However, real-world graphs invariably contain a certain proportion of heterophilous nodes, c…

cs.LG2023★ 13 cited

Neighborhood Homophily-based Graph Convolutional Network

Shengbo Gong, Jiajun Zhou, Chenxuan Xie +1

Graph neural networks (GNNs) have been proved powerful in graph-oriented tasks. However, many real-world graphs are heterophilous, challenging the homophily assumption of classical…

cond-mat.mtrl-sci2022★ 3 cited

A cloud platform for automating and sharing analysis of raw simulation data from high throughput polymer molecular dynamics simulations

Tian Xie, Ha-Kyung Kwon, Daniel Schweigert +9

Open material databases storing hundreds of thousands of material structures and their corresponding properties have become the cornerstone of modern computational materials scienc…

cond-mat.mtrl-sci2022★ 2 cited

Examining graph neural networks for crystal structures: limitations and opportunities for capturing periodicity

Sheng Gong, Tian Xie, Yang Shao-Horn +2

Historically, materials informatics has relied on human-designed descriptors of materials structures. In recent years, graph neural networks (GNNs) have been proposed for learning…

cs.CR2021★ 2 cited

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…