InvariantFeatures

Implementation of Invariant Features based on the field generators of invariant polynomials for O(d) x S_n, specifically

• Conjugation-Invariant DeepSet (CI-DS)
• $O(d)$-Invariant DeepSet (OI-DS)

Dependencies

• Python 3.7+
• Pytorch 1.10+
• pytorch-geometric version 2.4.x

You can follow the code below to install pytorch-geometric

import os
import torch
os.environ['TORCH'] = torch.__version__
pip install -q torch-scatter -f https://data.pyg.org/whl/torch-${TORCH}.html
pip install -q torch-sparse -f https://data.pyg.org/whl/torch-${TORCH}.html
pip install -q torch-cluster -f https://data.pyg.org/whl/torch-${TORCH}.html
pip install -q git+https://github.com/pyg-team/pytorch_geometric.git

Experiments

• To run experiment on QM7b (Section 5.1): python runRegression.py --target [TARGET_INDEX]
• To run experiment on GW distance regression (Section 5.1): Pointcloud_GWdist.ipynb
  • ModelNet40 data (sub-sampling with 100 points) here
  • Computed GW distances from ModelNet40, subset of class 2 and 7: train set, test set