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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,738 papers · 148 categories

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0111 · May 202419922001200920172026
3 results for “Procrustes-Wasserstein”
An in depth look at the Procrustes-Wasserstein distance: properties and barycentersstat.ML

A new method for computing shape barycenters from point clouds using Procrustes-Wasserstein distance.

problem Computing representative shapes from point clouds with precise alignment and shape preservation.
method Developed a new distance metric (Procrustes-Wasserstein) and algorithms for computing barycenters.
result Superior performance in precise alignment and shape preservation compared to existing OT approaches.
Procrustes-Wassersteindistancebarycenterpoint cloudsrigid transformations
2025-07-01abs ↗pdf ↗
Aligning Embeddings and Geometric Random Graphs: Informational Results and Computational Approaches for the Procrustes-Wasserstein Problemstat.ML

Study matches two noisy point clouds with geometric transformations and relabeling.

problem Matching two noisy point clouds with orthogonal transformations and relabeling.
method Information-theoretic results and Ping-Pong algorithm for computational alignment.
result The Ping-Pong algorithm retrieves the planted signal after one step.
Procrustes-Wasserstein problemgeometric random graphseuclidean transport costhigh-dimensional dataunsupervised learning
2024-05-23abs ↗pdf ↗
Procrustes Wasserstein Metric: A Modified Benamou-Brenier Approach with Applications to Latent Gaussian Distributionsstat.ML

Modified Wasserstein metric for Gaussian distributions, invariant to isometries.

problem Distance measurement for latent Gaussian distributions invariant to isometries.
method Modified Benamou-Brenier approach leading to a Procrustes Wasserstein metric.
result For Gaussian distributions, the metric reduces to Euclidean distance between eigenvalues.
Wasserstein metricBenamou-BrenierGaussian distributionsisometrieslatent variables
2025-03-20abs ↗pdf ↗