Graph neural networks: foundation, frontiers and applications
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …
recent years. Graph neural networks, also known as deep learning on graphs, graph …
Brain network similarity: methods and applications
Graph theoretical approach has proved an effective tool to understand, characterize, and
quantify the complex brain network. However, much less attention has been paid to methods …
quantify the complex brain network. However, much less attention has been paid to methods …
Sub-graph contrast for scalable self-supervised graph representation learning
Y Jiao, Y **-based interpretable neural network for classification of limited, noisy brain data
Map** the human brain, or understanding how certain brain regions relate to specific
aspects of cognition, has been and remains an active area of neuroscience research …
aspects of cognition, has been and remains an active area of neuroscience research …
Heterogeneous graph matching networks
Information systems have widely been the target of malware attacks. Traditional signature-
based malicious program detection algorithms can only detect known malware and are …
based malicious program detection algorithms can only detect known malware and are …