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CellEncoding Lifting (Cell to Graph) #12
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Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #12 +/- ##
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Coverage ? 63.92%
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Files ? 15
Lines ? 474
Branches ? 0
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Hits ? 303
Misses ? 171
Partials ? 0 ☔ View full report in Codecov by Sentry. |
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Hello @aweers! Thank you for your submission. As we near the end of the challenge, I am collecting participant info for the purpose of selecting and announcing winners. Please email me (or have one member of your team email me) at guillermo_bernardez@ucsb.edu so I can share access to the voting form. In your email, please include:
Before July 12, make sure that your submission respects all Submission Requirements laid out on the challenge page. Any submission that fails to meet this criteria will be automatically disqualified. |
Implementation of the Cell to Graph Lifting via Cell Encoding as proposed in Reducing learning on cell complexes to graphs by Jogl, F., Thiessen, M., & Gärtner, T.
Short description:$X$ as source domain and transforms it to a graph $G_X$ as destination domain. Each cell $P_X$ becomes a vertex in $G_X$ , such that $V_X=P_X$ . Those vertices are connected via two rules:
The lifting takes a cell complex
If either rule applies to a pair of cells, their corresponding vertices in$G_X$ get connected with an edge.
Additionally each vertex gets an encoding that corresponds to the one-hot encoded cell dimension.