Hello!
I am working on 3D point clouds. I have the SPARSE MATRIX representation of the graph structure of the point cloud (like csr_matrix in scipy.sparse). I want to club together the points that are within certain threshold of the Geodesic distance (approximated by the path length in the graph) and process them together. TO FIND such points, I need to run some shortest path finding algorithm like Dijkstra's. In a nutshell, my idea is like this
1) Sample K points out of N points (that I could do using Furthest Point Sampling)
2) Find the nearest Geodesic neighbours (using BackProp supported algorithm) for each of K points
3) Process the neighbours for each point using some Neural Network

This will go in my forward function.
Is there a way to implement Dijkstra’s(that support BackProp) in my functionality?
Or any other idea that I can implement?
Thank you!