Similar to Seq2Seq models, are there graph2graph models available?
Context: I am working on a dimension reduction problem on shapes, where,
- shapes are represented as graph,
- vertices as nodes,
- connecting curves as edges.
- dimension reduction operation is called as Midcurve generation.
- Input is 2D profile, say a closed polygon. Example: thick ‘L’ profile on left in the image below.
- Output is 1D curve in the middle of the profile. Example: thin ‘L’ curve on the right in the image below
Wish to build encoder-decoder network which accepts graphs as input as well as output.
I have training set of such input and output graphs, a supervised set.
As I could not find ready graph2graph network, I converted the problem to image2image (say, pix2pix like) and then solving it. But wish to investigate if graph2graph network is available or not.
More info:
- Short paper: MidcurveNN: Encoder-Decoder Neural Network for Computing Midcurve of a Thin Polygon, viXra.org e-Print archive, viXra:1904.0429
- Github repo, source code: GitHub - yogeshhk/MidcurveNN: Computation of Midcurve of Thin Polygons using Neural Networks
How to build such encoder decode network? Please note that as both, input and output are different, this can not be AutoEncoder.
Any ideas?