pytorch-topological
pytorch-topological copied to clipboard
Make TOGL feature complete
Currently, the implementation of TOGL ignores the following features:
- handling higher-order information properly
- expanding simplicial complexes
- making use of the dimension of features
Some of these are rather tough to handle; this should probably rather become a project on its own. In the original paper, for instance, we are not actually going beyond dimension 1 in terms of features, so I am somewhat loath to mix the re-implementation of TOGL with new feature development. A good starting point would be to see how to capture 1-dimensional information; in my current implementation, I figured that I could get this stuff much more easily by using a lower star filtration.
Hi @Pseudomanifold, is this a good place to pick up on where we left off in BorgwardtLab/TOGL#13, or should I open a new ticket?
Sure!
Thanks! You mentioned that TOGL isn't complete yet during our discussion. What is missing? What features do you need added?
Potentially some other aggregation functions would be useful; I also have not tried out how easy it is to include this type of layer into arbitrary GNNs. Except for the aggregation functions, I think this is relatively in sync with the other code, though.