python3-torch-cluster
PyTorch extension library of optimized graph cluster algorithms (Python 3)
Description
This package consists of a small extension library of highly optimized graph cluster algorithms for the use in PyTorch. The package consists of the following clustering algorithms: * Graclus from Dhillon et al.: Weighted Graph Cuts without Eigenvectors: A
Multilevel Approach
* Voxel Grid Pooling from, e.g., Simonovsky and Komodakis: Dynamic
Edge-Conditioned Filters in Convolutional Neural Networks on Graphs
* Iterative Farthest Point Sampling from, e.g. Qi et al.: PointNet++: Deep
Hierarchical Feature Learning on Point Sets in a Metric Space
* k-NN and Radius graph generation
* Clustering based on nearest points
* Random Walk Sampling from, e.g., Grover and Leskovec: node2vec: Scalable
Feature Learning for Networks
All included operations work on varying data types and are implemented both
for CPU and GPU.
This package installs the library for Python 3.Upload more screenshots
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Homepage
https://github.com/rusty1s/pytorch_cluster
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