14 citations · 30 across the 11 of their papers we have counts for
4 papers · 1 filter
Unbalanced Optimal Transport, from Theory to Numerics
Thibault Séjourné, Gabriel Peyré, François-Xavier Vialard
Optimal Transport (OT) has recently emerged as a central tool in data sciences to compare in a geometrically faithful way point clouds and more generally probability distributions.…
Smooth over-parameterized solvers for non-smooth structured optimization
Clarice Poon, Gabriel Peyré
Non-smooth optimization is a core ingredient of many imaging or machine learning pipelines. Non-smoothness encodes structural constraints on the solutions, such as sparsity, group…
Do Residual Neural Networks discretize Neural Ordinary Differential Equations?
Michael E. Sander, Pierre Ablin, Gabriel Peyré
Neural Ordinary Differential Equations (Neural ODEs) are the continuous analog of Residual Neural Networks (ResNets). We investigate whether the discrete dynamics defined by a ResN…
Faster Unbalanced Optimal Transport: Translation invariant Sinkhorn and 1-D Frank-Wolfe
Thibault Séjourné, François-Xavier Vialard, Gabriel Peyré
Unbalanced optimal transport (UOT) extends optimal transport (OT) to take into account mass variations to compare distributions. This is crucial to make OT successful in ML applica…