Source code for our paper "Pseudoinverse Graph Convolutional Networks: Fast Filters Tailored for Large Eigengaps of Dense Graphs and Hypergraphs," published in Springer Data Mining and Knowledge Discovery (2021).
To use this code, install the required Python packages torch and torch_geometric and run python setup.py build and python setup.py install.
All results in the paper were generated with the scripts in the experiments directory. For usage, see the following instructions:
- For point clouds:
python run-pointcloud.py -h - For hypergraphs:
python run-hypergraph.py -h - For sparse graphs:
python run-graph.py -h