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Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformers

By Doron Haviv and others
Optimal transport (OT) and the related Wasserstein metric (W) are powerful and ubiquitous tools for comparing distributions. However, computing pairwise Wasserstein distances rapidly becomes intractable as cohort size grows. An attractive alternative would be to find an embedding space in which pairwise Euclidean distances map to OT distances, akin to... Show more
June 4, 2024
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Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformers
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