Entropic RNOT learns a neural pullback parameterization of the target Schrödinger potential to recover entropic OT couplings on Riemannian manifolds and construct convergent transport surrogates with fixed-regularization guarantees.
The expressive power of neural networks: A view from the width.arXiv [cs.LG], September 2017
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Entropic Riemannian Neural Optimal Transport
Entropic RNOT learns a neural pullback parameterization of the target Schrödinger potential to recover entropic OT couplings on Riemannian manifolds and construct convergent transport surrogates with fixed-regularization guarantees.