70 citations · 170 across the 13 of their papers we have counts for
5 papers · 1 filter
Heterogeneous manifolds for curvature-aware graph embedding
Francesco Di Giovanni, Giulia Luise, Michael Bronstein
Graph embeddings, wherein the nodes of the graph are represented by points in a continuous space, are used in a broad range of Graph ML applications. The quality of such embeddings…
Generalization Properties of Optimal Transport GANs with Latent Distribution Learning
Giulia Luise, Massimiliano Pontil, Carlo Ciliberto
The Generative Adversarial Networks (GAN) framework is a well-established paradigm for probability matching and realistic sample generation. While recent attention has been devoted…
A Non-Asymptotic Analysis for Stein Variational Gradient Descent
Anna Korba, Adil Salim, Michael Arbel +2
We study the Stein Variational Gradient Descent (SVGD) algorithm, which optimises a set of particles to approximate a target probability distribution on $\mathbb{…
Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm
Giulia Luise, Saverio Salzo, Massimiliano Pontil +1
We present a novel algorithm to estimate the barycenter of arbitrary probability distributions with respect to the Sinkhorn divergence. Based on a Frank-Wolfe optimization strategy…
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance
Giulia Luise, Alessandro Rudi, Massimiliano Pontil +1
Applications of optimal transport have recently gained remarkable attention thanks to the computational advantages of entropic regularization. However, in most situations the Sinkh…