Fix #2495 - Fix PPCA noise variance dilution and null-space leakage in MorphologicalDeviationScore#2496
Open
akenmorris wants to merge 2 commits intomasterfrom
Open
Fix #2495 - Fix PPCA noise variance dilution and null-space leakage in MorphologicalDeviationScore#2496akenmorris wants to merge 2 commits intomasterfrom
akenmorris wants to merge 2 commits intomasterfrom
Conversation
…n MorphologicalDeviationScore The PPCA noise variance divides by (d - q) instead of (rank - q), where d includes ~5950 structurally zero dimensions from the null space (e.g. for 2048 particles). This dilutes the estimate ~34× (scales linearly with particle count). The Woodbury-based precision matrix then applies this diluted 1/o^2 to all d dimensions including the null space, so most of the score is coming from insignificant and noise dimensions. - Correct denominator to (rank - q) — average only over estimable eigenvalues - Project into the rank-dimensional subspace instead of building a d × d precision matrix, eliminating null-space contributions entirely
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
The PPCA noise variance divides by (d - q) instead of (rank - q), where d includes ~5950 structurally zero dimensions from the null space (e.g. for 2048 particles). This dilutes the estimate ~34× (scales linearly with particle count). The Woodbury-based precision matrix then applies this diluted 1/o^2 to all d dimensions including the null space, so most of the score is coming from insignificant and noise dimensions.