The general consensus for an Graph-AE is to train against the dense adjacency matrix. However, you only need a dense output. In contrast, the input graph can be sparse. We have an example of this, see ...

Repository to create a PyTorch Geometric graph from scratch Requirements (Anaconda) Python 3.6 pandas torch torch_geometric Excel Instructions This is a simple code to transform a graph (via it's ...

In this paper, we propose a progressive two-step algorithm called GIFTS to accelerate GCN inference on CPUs by making use of the dynamic sparsity in the feature matrix and the static sparsity in the ...

In this paper, we describe three graph theoretic heuristics that attempt to determine an optimal planar adjacency graph from a REL chart. Our computational experience suggests that these methods can ...