SPOTLIGHTS 5 x 10 -> Quentin Berthet and Jonathan Niles-Weed, Estimation of smooth densities in Wasserstein distance -> David Alvarez-Melis, Youssef Mroueh and Tommi Jaakkola, Unsupervised Hierarchy Matching with Optimal Transport over Hyperbolic spaces ->Alex Delalande and Quentin Mérigot, Linearization of the 2-Wasserstein space and stability of optimal transport maps ->Ashok Makkuva, Amirhossein Taghvaei, Sewoong Oh and Jason Lee, Optimal transport mapping via input convex neural networks ->Dirk Lorenz and Hinrich Mahler, Orlicz-space regularization for optimal transport and algorithms for quadratic regularization ->John Lee, Nicholas Bertrand and Christopher Rozell, Parallel Unbalanced Optimal Transport Regularization for Imaging ->Youssef Mroueh, Wasserstein Style Transfer ->Max Dabagia and Eva Dyer, Barycenters in the brain: An optimal transport approach to modeling connectivity ->Tudor Manole, Sivaraman Balakrishnan and Larry Wasserman, Minimax Confidence Intervals for the Sliced Wasserstein Distance ->Mukul Bhutani, Thomas Magelinski and Zico Kolter, Sinkhorn-Flow: Predicting Probability Mass Flow in Dynamical Systems Using Optimal Transport