Linearized Wasserstein dimensionality reduction with approximation guarantees
LOT Wassmap is a computationally efficient algorithm for finding low-dimensional structures in Wasserstein space, where data is treated as probability measures. It uses linearized optimal transport approximations, like Sinkhorn distances, to avoid expensive pairwise distance matrix computations. The method provides theoretical guarantees on embedding quality even when explicit measure descriptions are unavailable.