Graph polynomials serve as robust algebraic encodings of the intricate combinatorial properties inherent to graphs. At the heart of this discipline lies the Tutte polynomial, an invariant that not ...
Download PDF Join the Discussion View in the ACM Digital Library EXAMPLE 2. A standard way of representing graphs is by their adjacency matrices; once we have an adjacency matrix we can obtain a {0, 1 ...
This project allows users to dynamically create and plot polynomial functions of varying degrees with user-defined coefficients and intercepts. The graph shows the polynomial curve along with the ...
Abstract: We investigate graph convolution networks with efficient learning from higher-order graph convolutions and direct learning from adjacency matrices for node classification. We revisit the ...
Abstract: Graph Fourier transform centrality (GFTC) is a valuable tool for identifying influential nodes within complex networks. However, applying the graph Fourier transform (GFT) to compute node ...
The main contribution of this work is a novel graph rewiring framework that simultaneously reduces over-squashing, respects graph locality, and preserves sparsity, outperforming existing techniques on ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback