36 citations · 48 across the 22 of their papers we have counts for
25 papers
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…
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…
Transformers for Tabular Data: A Training Perspective of Self-Attention via Optimal Transport
Alessandro Quadrio, Antonio Candelieri
This thesis examines self-attention training through the lens of Optimal Transport (OT) and develops an OT-based alternative for tabular classification. The study tracks intermedia…
Structural Vulnerability Assessment in Urban Transport Networks: A Network-Wide Geometric Approach Using Gromov-Wasserstein
Iman Seyedi, Antonio Candelieri, Enza Messina +1
Urban transportation networks are inherently vulnerable to disruptions that affect connectivity and passenger mobility. Traditional graph_theoretic metrics, such as betweenness and…
Gromov-Wasserstein and optimal transport: from assignment problems to probabilistic numeric
Iman Seyedi, Antonio Candelieri, Enza Messina +1
The assignment problem, a cornerstone of operations research, seeks an optimal one-to-one mapping between agents and tasks to minimize total cost. This work traces its evolution fr…