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06/28/2022
Supervised Training of Conditional Monge Maps
Optimal transport (OT) theory describes general principles to define and...
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06/15/2022
Rethinking Initialization of the Sinkhorn Algorithm
Computing an optimal transport (OT) coupling between distributions plays...
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06/02/2021
Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs
The ability to compare and align related datasets living in heterogeneou...
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04/26/2020
Noisy Adaptive Group Testing using Bayesian Sequential Experimental Design
When test resources are scarce, a viable alternative to test for the pre...
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02/05/2020
Fast and Robust Comparison of Probability Measures in Heterogeneous Spaces
The problem of comparing distributions endowed with their own geometry a...
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09/30/2019
On the Complexity of Approximating Multimarginal Optimal Transport
We study the complexity of approximating the multimarginal optimal trans...
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05/28/2019
Differentiable Sorting using Optimal Transport:The Sinkhorn CDF and Quantile Operator
Sorting an array is a fundamental routine in machine learning, one that ...
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01/25/2019
Subspace Robust Wasserstein distances
Making sense of Wasserstein distances between discrete measures in high-...
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03/05/2017
Soft-DTW: a Differentiable Loss Function for Time-Series
We propose in this paper a differentiable learning loss between time ser...
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06/04/2013
