12 citations · 25 across the 30 of their papers we have counts for
3 papers · 1 filter
Transport-based Counterfactual Models
Lucas de Lara, Alberto González-Sanz, Nicholas Asher +2
Counterfactual frameworks have grown popular in machine learning for both explaining algorithmic decisions but also defining individual notions of fairness, more intuitive than typ…
Central Limit Theorems for General Transportation Costs
Eustasio del Barrio, Alberto González-Sanz, Jean-Michel Loubes
We consider the problem of optimal transportation with general cost between a empirical measure and a general target probability on R d , with d 1. We extend results in [19]…
A Consistent Extension of Discrete Optimal Transport Maps for Machine Learning Applications
Lucas de Lara, Alberto González-Sanz, Jean-Michel Loubes
Optimal transport maps define a one-to-one correspondence between probability distributions, and as such have grown popular for machine learning applications. However, these maps a…