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2 votes
Accepted

Understanding the node information score in the paper "Hierarchical Graph Pooling with Structure Learning"

Here, $H$ is a $n * d$ matrix where $n$ is the number of total nodes in the graph and $d$ is the dimension of embedding of each node. Using the notation in the question, the basic GNN formulation ...
user1825567's user avatar
1 vote

Why should one focus on spectral operations as a computer vision researcher?

The main advantage of using spectral operations comes from the Covolution theorem, which states that the Fourier transform of the convolution of two functions is equal to the pointwise multiplication ...
Edoardo Guerriero's user avatar
1 vote
Accepted

What exactly is the eigenspace of a graph (in spectral clustering)?

In spectral clustering we not find the eigenvectors of a graph (a graph is not a matrix) but the eigenvalues/eigenvectors of the Laplacian matrix related to the adjacency matrix of the graph: graph =&...
pasaba por aqui's user avatar

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