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.
Analytic and geometric background of recurrence and non-explosion of the brownian motion on riemannian manifolds.Bull
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ML 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.