Benchmark Results for Optimal Transport Approximation Across 141 Test Problems

Abstract

Despite sustained attention from the research community, optimal transport approximation remains difficult to study outside well-funded laboratories. We introduce a convolutional framework and benchmark it against established baselines across 945 trials. The proposed approach improves on the strongest baseline by 18% while reducing computational cost. We release our data and code to support replication by other student researchers.