3 citations · 3 across the 2 of their papers we have counts for
2 papers
stat.ML2023
Gromov-Wasserstein-like Distances in the Gaussian Mixture Models Space
Antoine Salmona, Julie Delon, Agnès Desolneux
The Gromov-Wasserstein (GW) distance is frequently used in machine learning to compare distributions across distinct metric spaces. Despite its utility, it remains computationally…
stat.ML2022★ 3 cited
Can Push-forward Generative Models Fit Multimodal Distributions?
Antoine Salmona, Valentin de Bortoli, Julie Delon +1
Many generative models synthesize data by transforming a standard Gaussian random variable using a deterministic neural network. Among these models are the Variational Autoencoders…