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  • Introduction to on Entropic Optimal Transport
    The basic idea is to solve this “entropic” optimal transport problem for small ε > 0 to obtain an approximation of the (unregularized) optimal transport problem that corresponds to ε = 0
  • Marcel Nutz - Publications
    Quantitative Convergence of Quadratically Regularized Linear Programs
  • Entropic Optimal Transport - Class Central
    Explore entropic optimal transport with Prof Marcel Nutz, delving into advanced mathematical concepts and their applications in economics and probability theory
  • Stability of Entropic Optimal Transport and Convergence of Sinkhorn’s . . .
    Entropic optimal transport: Geometry and large deviations Duke Math J , to appear Quantitative stability of regularized optimal transport and convergence of Sinkhorn’s algorithm Preprint arXiv:2110 06798 P Ghosal, M Nutz, and E Bernton Stability of entropic optimal transport and Schrödinger bridges J Funct Anal , to appear
  • Entropic Optimal Transport: Geometry and Large Deviations
    Our arguments are based on the geometry of the optimizers and inspired by the use of c-cyclical monotonicity in classical transport theory The results can also be phrased in terms of Schrödinger bridges
  • Entropic Optimal Transport - Sciences Po
    Abstract We discuss entropically regularized optimal transport in two regimes First, the convergence to the (unregularized) optimal transport problem as the regulariza- tion parameter vanishes, both of the optimal couplings and the dual potentials Second, the stability of entropic optimal transport with respect to the marginals
  • Stability of entropic optimal transport and Schrödinger bridges
    This text develops mathematical foundations for entropic optimal transport and Sinkhorn’s algorithm in a self-contained yet general way It is a revised version of lecture notes from a course given…
  • Entropic Optimal Transport: Geometry and Large Deviations
    The resulting entropic optimal transport problem provides an approximate optimal trans-port when solved for small regularization parameter " > 0 while admitting much more efficient algorithms than the unregularized problem, in addition to having other desirable properties





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