Median-Normalized Weak Pushforward Potential Training
Represent the quadratic OT potential with a strongly convex input-convex neural network and train it by matching the distribution of its gradient pushforward to the target distribution in a weak dual metric. Median-center the potential on every minibatch so that optimization does not waste capacity or suffer instability from the additive constant ambiguity. The paper's stability inequality predicts that this can produce a more stable potential estimate than directly optimizing a transport-map…