5 citations · 9 across the 17 of their papers we have counts for
4 papers · 1 filter
Fused ultrametric Gromov-Wasserstein for Scenario Tree generation in Multistage Stochastic Programming
Antonio Candelieri, Iman Seyedi, Francesco Archetti
Multistage Stochastic Programming requires scenario trees that accurately approximate the unknown underlying uncertainty process without violating the non-anticipativity constraint…
Diffusion enabled Optimal Transport distances for graph matching
Iman Seyedi, Francesco Archetti
This paper introduces Diffusion Semi-Relaxed Fused Gromov-Wasserstein (DsrFGW), a novel method for graph comparison that unifies node features and structural connectivity through o…
Wasserstein-enabled characterization of designs and myopic decisions in Bayesian Optimization
Antonio Candelieri, Francesco Archetti
Impractical assumptions, an inherently myopic nature, and the crucial role of the initial design, all together contribute to making theoretical convergence proofs of little value i…
Weighted Wasserstein Barycenter of Gaussian Processes for exotic Bayesian Optimization tasks
Antonio Candelieri, Francesco Archetti
Exploiting the analogy between Gaussian Distributions and Gaussian Processes' posterior, we present how the weighted Wasserstein Barycenter of Gaussian Processes (W2BGP) can be use…