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cs.LG2026

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…

cs.LG2026

Conformal Disentanglement and Latent-Space Curation: A Neural Framework for Perspective Synthesis, Differentiation and Targeted Generation

George A. Kevrekidis, Eleni D. Koronaki, Dimitris G. Giovanis +1

Many scientific and engineering problems involve observing a common phenomenon through multiple heterogeneous sensors or measurement modalities. Such observations typically contain…

cs.LG2025

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…

cs.LG2025

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…

cs.LG2025

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…

cs.LG2025

Neural Operators for Stochastic Modeling of Nonlinear Structural System Response to Natural Hazards

Somdatta Goswami, Dimitris G. Giovanis, Bowei Li +2

Traditionally, neural networks have been employed to learn the mapping between finite-dimensional Euclidean spaces. However, recent research has opened up new horizons, focusing on…