ENOT: Expectile Regularization for Fast and Accurate Training of Neural Optimal Transport

One notable advantage of using OT in the latter setting is that, compared to other generative approaches, such as GANs, Normalizing Flows, or Diffusion Models, there is no assumption for one of the measures to be defined in a closed form ( e.g., Gaussian or uniform)