feat: added kernel density estimation to score matching. #258
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tl82649
reviewed
Nov 30, 2023
coreax/score_matching.py
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| return children, aux_data | ||
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| def match(self, x: ArrayLike) -> Callable: |
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If x is not used, should we put x: ArrayLike | None = None? Then we don't need to call match with anything; particularly in test_score_matching.py.
tl82649
reviewed
Nov 30, 2023
tests/unit/test_score_matching.py
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| # Extract the score function (this is not really learned from the data, more | ||
| # defined within the object) | ||
| learned_score = kernel_density_matcher.match(samples) |
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If comment here is followed, we shouldn't need the match argument.
Repeat for all other calls to match in TestKernelDensityMatching.
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Updated to not input anything (since it's unused)
tl82649
requested changes
Nov 30, 2023
tl82649
approved these changes
Dec 6, 2023
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Refs: 257
PR Type
Description
When converting kernel.py to OOP, we removed the functionality to (easily) estimate a score function via kernel density estimation. This has been added back into score_matching.py to provide an alternative to the neural network approach.
How Has This Been Tested?
Added test class
TestKernelDensityMatchingwith:Test A: test_univariate_gaussian_score
Test B: test_multivariate_gaussian_score
Test C: test_univariate_gmm_score
Test D: test_multivariate_gmm_score
Does this PR introduce a breaking change?
No
Checklist before requesting a review