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8 papers · 1 filter
Learning Monge maps with constrained drifting models
Théo Dumont, Théo Lacombe, François-Xavier Vialard
We study the estimation of optimal transport (OT) maps between an arbitrary source probability measure and a log-concave target probability measure. Our contributions are twofold.…
Fast Large Deformation Matching with the Energy Distance Kernel
Siwan Boufadene, François-Xavier Vialard, Jean Feydy
We propose an efficient framework for point cloud and measure registration using bi-Lipschitz homeomorphisms, achieving O(n log n) complexity, where n is the number of points. By l…
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…
Metric completion of with the right-invariant metric
Simone Di Marino, Andrea Natale, Rabah Tahraoui +1
We consider the group of smooth increasing diffeomorphisms Diff on the unit interval endowed with the right-invariant metric. We compute the metric completion of this space w…
A Variational Bayesian Approach for Image Restoration. Application to Image Deblurring with Poisson-Gaussian Noise
Yosra Marnissi, Yuling Zheng, Emilie Chouzenoux +1
In this paper, a methodology is investigated for signal recovery in the presence of non-Gaussian noise. In contrast with regularized minimization approaches often adopted in the li…
Euclid in a Taxicab: Sparse Blind Deconvolution with Smoothed l1/l2 Regularization
Audrey Repetti, Mai Quyen Pham, Laurent Duval +2
The l1/l2 ratio regularization function has shown good performance for retrieving sparse signals in a number of recent works, in the context of blind deconvolution. Indeed, it bene…