Research map / Learning theory and algorithms / Optimal transport
Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use Wasserstein Singular Vectors instead of Kernel PCA / ℓ² distances | PBMC 3k cell distances · PBMC 3k cells | ASW: 0.241 -> 0.348 | Helped |
| Use Wasserstein Singular Vectors instead of Gene2Vec / ℓ² distances | PBMC 3k marker-gene distances · PBMC 3k marker genes | ASW: 0.0186 -> 0.136 | Helped |
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