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CellEncoding Lifting (Cell to Graph) #12

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@aweers aweers commented Jun 9, 2024

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:
The lifting takes a cell complex $X$ 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:

  1. Two cells $\tau, \delta \in P_X$ have a direct boundary relationship.
  2. Two cells $\tau, \delta \in P_X$ share a common higher-dimensional cell.

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.

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@gbg141 gbg141 marked this pull request as ready for review July 1, 2024 11:03
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gbg141 commented Jul 8, 2024

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:

  • your first and last name (as well as any other team members)
  • the title of the method you implemented
  • the input domain of the method you implemented
  • the output domain of the method you implemented
  • your pull request number (CellEncoding Lifting (Cell to Graph) #12)

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.

@gbg141 gbg141 added award-category-2 Lifting to Combinatorial, Hypergraph or Graph Domain award-category-4 Connectivity-based Lifting labels Jul 9, 2024
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3 participants