This package consists of a small extension library of highly optimized graph cluster algorithms for the use in [PyTorch](http://pytorch.org/).
This package consists of a small extension library of highly optimized graph cluster algorithms for the use in [PyTorch](http://pytorch.org/).
The package consists of the following clustering algorithms:
The package consists of the following clustering algorithms:
***[Graclus](#graclus)**
***[Graclus](#graclus)** from Dhillon *et al.*: [Weighted Graph Cuts without Eigenvectors: A Multilevel Approach](http://www.cs.utexas.edu/users/inderjit/public_papers/multilevel_pami.pdf)(PAMI 2007)
***[VoxelGrid](#voxelgrid)**
***[VoxelGrid](#voxelgrid)**
All included operations work on varying data types and are implemented both for CPU and GPU.
All included operations work on varying data types and are implemented both for CPU and GPU.
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@@ -34,6 +34,7 @@ pip install cffi torch-cluster
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@@ -34,6 +34,7 @@ pip install cffi torch-cluster
## Graclus
## Graclus
A greedy clustering algorithm of picking an unmarked vertex and matching it with one its unmarked neighbors (that maximizes its edge weight).
A greedy clustering algorithm of picking an unmarked vertex and matching it with one its unmarked neighbors (that maximizes its edge weight).
The GPU algorithm is adapted from Fagginger Auer and Bisseling: [A GPU Algorithm for Greedy Graph Matching](http://www.staff.science.uu.nl/~bisse101/Articles/match12.pdf)(LNCS 2012)
