EricZQu/Hyperbolic-Convolution-via-Kernel-Point-Aggregation

Hyperbolic Convolution via Kernel Point Aggregation

This repo provides the official implementation of the HKConv from the following paper.

Hyperbolic Convolution via Kernel Point Aggregation
Eric Qu, Dongmian Zou
arXiv: https://arxiv.org/abs/2306.08862

Environment

The code is tested on Python 3.9, PyTorch 1.12.1, and CUDA 11.3.

First, install PyTorch from https://pytorch.org/. Then, install the other dependencies by

pip install -r requirements.txt

Training

The training scripts are in scripts\. You can use them by

bash scripts/experiment/dataset.experiment.sh

File Descriptions

data/: Datasets
distribution/: Hyperbolic Distributions
kernels/: Kernel generation
layers/: Hyperbolic layers
manifolds/: Manifold calculations
models/: GNN models
optim/: Optimization on manifolds
scripts/: Training scripts
utils/: Utility files
train.py: Training scripts

Our HKConv is located in layers/hyp_layers.py.