Find out how today's engineers succeed by growing their technical abilities, improving how they communicate, and staying open ...

What is this book about? Graph neural networks are a highly effective tool for analyzing data that can be represented as a graph, such as social networks, chemical compounds, or transportation ...

When programmers write project code, they may copy or reference some open-source code, which may include defective code, causing vulnerabilities in the project. This causes a potential threat to the ...

Graph neural networks are a highly effective tool for analyzing data that can be represented as a graph, such as social networks, chemical compounds, or transportation networks. The past few years ...

The application of Graph Neural Networks for pre-training models for source code is not well studied. We experimented with pre-training a Graph Neural Network model for Python on tasks of Name ...

Deep learning techniques are used for data with an underlying non-Euclidean structure, such as graphs or manifolds, and are known as deep geometric learning. These techniques have previously been used ...