Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance

Applications of optimal transport have recently gained remarkable attention thanks to the computational advantages of entropic regularization. However, in most situations the Sinkhorn approximation of the Wasserstein distance is replaced by a regularized version that is less accurate but easy to differentiate... (read more)

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