You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
The continuous/continuous case of algebraic combination (aka "convolution") is currently really slow. There are several opportunities for quality and speedup. At a minimum:
Intelligent downsampling before starting the convolution
Better target points (via some sort of clustering or binning?)
Use of triangular kernels for adding up the results, and a tree structure (B-tree?) for the target nodes. The current implementation uses Gaussian kernels and is O(M × N) sloooow.
The text was updated successfully, but these errors were encountered:
I think I feel fairly uncomfortable about convolution and the challenges it seems to bring. It seems like it introduces a fair number of edge cases, and it's not obviously it's more worthy of investment than sampling at these points.
The continuous/continuous case of algebraic combination (aka "convolution") is currently really slow. There are several opportunities for quality and speedup. At a minimum:
The text was updated successfully, but these errors were encountered: