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: We prove that polynomial calculus (and hence also Nullstellensatz) over any field requires linear degree to refute that sparse random regular graphs, as well as sparse Erdős-Rényi random ...

This repository provides the codebase used to study the behavior of graph Laplacian mutual coherence over Erdős–Rényi and sensor graphs. It evaluates the accuracy of the upper and lower bounds ...

pip install torch_geometric pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv \ -f https://data.pyg.org/whl/torch-2.6.0+cu124.html ...