59 citations · 109 across the 17 of their papers we have counts for
17 papers
Generative Learning of Separatrices
Ellis R. Crabtree, Dimitris G. Giovanis, Anastasia Georgiou +2
The identification and reconstruction of the boundaries separating basins of attraction in multistable, multidimensional dynamical systems presents a fundamental challenge in compu…
Conformalized Polynomial Chaos Expansion for Uncertainty-aware Surrogate Modeling
Dimitrios Loukrezis, Dimitris G. Giovanis
This work introduces a method to equip data-driven polynomial chaos expansion surrogate models with intervals that quantify the predictive uncertainty of the surrogate. To that end…
On Some Tunable Multi-fidelity Bayesian Optimization Frameworks
Arjun Manoj, Anastasia S. Georgiou, Dimitris G. Giovanis +2
Multi-fidelity optimization employs surrogate models that integrate information from varying levels of fidelity to guide efficient exploration of complex design spaces while minimi…
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 for Slow Manifolds and Bifurcation Diagrams
Ellis R. Crabtree, Dimitris G. Giovanis, Nikolaos Evangelou +2
In dynamical systems characterized by separation of time scales, the approximation of so called ``slow manifolds'', on which the long term dynamics lie, is a useful step for model…
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…