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2020-05-18Infer k when we pass the distances to the nearest neighborsMarc Glisse
2020-05-15Merge pull request #295 from yuichi-ike/weighted_ripsVincent Rouvreau
Weighted rips
2020-05-15Merge pull request #204 from MathieuCarriere/generatorsVincent Rouvreau
Generators
2020-05-12More testMarc Glisse
2020-05-12test + reformatMarc Glisse
2020-05-12reference and comments addedyuichi-ike
2020-05-11document and comments added, weights modifiedyuichi-ike
2020-04-30Merge pull request #285 from mglisse/wass-autodiffMarc Glisse
Automatic differentiation for Wasserstein distance
2020-04-29fix conflictMathieuCarriere
2020-04-29Merge remote-tracking branch 'origin/master' into gen2Marc Glisse
2020-04-28update outputMathieuCarriere
2020-04-28fix conflictMathieuCarriere
2020-04-28filtration value doubled, comments modifiedyuichi-ike
2020-04-22Reduce the probability of failure of test_dtmMarc Glisse
It is expected that hnsw sometimes misses one neighbor, which has an impact on the DTM, especially if the number of neighbors considered is low.
2020-04-22Test value of computed gradientMarc Glisse
2020-04-20Merge remote-tracking branch 'origin/master' into wass-autodiffMarc Glisse
2020-04-20Merge pull request #265 from mglisse/dtmMarc Glisse
DTM
2020-04-20Explicitly pass sort_results=True on some testsMarc Glisse
2020-04-20Reintroduce _proj_on_diag, with a unit testMarc Glisse
2020-04-19Test comparison with persistence_pairs()Marc Glisse
2020-04-19Drop redundant testMarc Glisse
torch.isnan(None) raises an exception anyway
2020-04-19Test gradientMarc Glisse
2020-04-18enable_autodiff for POT wasserstein_distanceMarc Glisse
2020-04-17Merge remote-tracking branch 'origin/master' into filtrationMarc Glisse
2020-04-14Check that the gradient is not NaNMarc Glisse
This can easily happen with pytorch, and there is special code to avoid it.
2020-04-14Merge remote-tracking branch 'origin/master' into dtmMarc Glisse
2020-04-14More testingMarc Glisse
2020-04-13enable_autodiff with keopsMarc Glisse
This doesn't seem like the best way to handle it, we may want to handle it like a wrapper that gets the indices from knn (whatever backend) and then computes the distances.
2020-04-12Parallelize the "precomputed" case of knnMarc Glisse
It is supposed to be possible to compile numpy with openmp, but it looks like it isn't done in any of the usual packages. It may be possible to refactor that code so there is less redundancy.
2020-04-11Use longer namesMarc Glisse
2020-04-07filtration value fixedyuichi-ike
2020-04-06Remove trailing whitespaceMarc Glisse
2020-04-06bug fixed, parameter name changedyuichi-ike
2020-04-06test_weighted_rips addedyuichi-ike
2020-03-31merged mastertlacombe
2020-03-31modified import in test to get consistent with gudhi.wasserstein.barycentertlacombe
2020-03-30Streamline initialize_filtrationMarc Glisse
2020-03-30Merge pull request #215 from MathieuCarriere/extended_persistenceMarc Glisse
Extended persistence
2020-03-28Default param of 2 for DTMMarc Glisse
2020-03-28Fix testMarc Glisse
2020-03-28Fix testMarc Glisse
2020-03-28Missing testMarc Glisse
2020-03-27docMarc Glisse
2020-03-27Improve coverageMarc Glisse
2020-03-26cmakeMarc Glisse
2020-03-24Remove min_persistence from generatorsMarc Glisse
It is supposed to be handled in persistence() already.
2020-03-23new fixesMathieuCarriere
2020-03-23Add testMarc Glisse
2020-03-22Merge master and fix conflictsROUVREAU Vincent
2020-03-19new fixesMathieuCarriere
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