The problem consists in classifying molecular graphs into two categories, depending on whether or not they exhibit a specific function. To tackle this, we aim to explore graph kernels for generating ...

You can create a release to package software, along with release notes and links to binary files, for other people to use. Learn more about releases in our docs.

Abstract: Kernel-based reconstruction of graph signals was extensively studied in graph signal processing domain, which has been which has been verified to be efficient for real-world applications.

Abstract: The authors combine feature-based kernel with extension path graph kernel into a multiple kernels learning method. Feature-based kernel method, extension path graph kernel method and ...