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Make TOGL feature complete #21
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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. |
Hello! I am also coming from the previous implementation of TOGL. I tried to carefully read the code but I struggle to identify what are the key differences between this implementation and the original one for TOGL. Would it be possible to have a few key points on the major differences between the two code bases? Best, |
The main difference is that the current implementation only supports aggregation based on deep sets. This is what works already: This is what is currently ignored: Hope that helps! |
Okay great thank you very much! |
Currently, the implementation of TOGL ignores the following features:
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