1 citations · 1 across the 3 of their papers we have counts for
3 papers
Enabling Probabilistic Learning on Manifolds through Double Diffusion Maps
Dimitris G Giovanis, Nikolaos Evangelou, Ioannis G Kevrekidis +1
We present a generative learning framework for probabilistic sampling based on an extension of the Probabilistic Learning on Manifolds (PLoM) approach, which is designed to generat…
Generative Learning of Densities on Manifolds
Dimitris G. Giovanis, Ellis Crabtree, Roger G. Ghanem +1
A generative modeling framework is proposed that combines diffusion models and manifold learning to efficiently sample data densities on manifolds. The approach utilizes Diffusion…
Transient anisotropic kernel for probabilistic learning on manifolds
Christian Soize, Roger Ghanem
PLoM (Probabilistic Learning on Manifolds) is a method introduced in 2016 for handling small training datasets by projecting an Itô equation from a stochastic dissipative Hamiltoni…