Age | Commit message (Collapse) | Author |
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DTM
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torch.isnan(None) raises an exception anyway
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This can easily happen with pytorch, and there is special code to avoid
it.
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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.
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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.
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Extended persistence
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wasserstein_distance.
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CMakeList to solve conflicts
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optimal matching in Wasserstein distance (pot) (Fix #203)
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Iterator over simplex tree
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extended_persistence
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About adding timedelay for feature engineering
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performed
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