59 citations · 109 across the 17 of their papers we have counts for
7 papers · 1 filter
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…
Guided Wave-Based Structural Awareness Under Varying Operating States via Manifold Representations
Yiming Fan, Dimitris G Giovanis, Fotis Kopsaftopoulos
Guided wave-based structural health monitoring (SHM) remains a powerful strategy for identifying early-stage defects and safeguarding vital aerospace structures. Yet, its practical…