20 citations · 20 across the 4 of their papers we have counts for
4 papers
Learning Effective Dynamics across Spatio-Temporal Scales of Complex Flows
Han Gao, Sebastian Kaltenbach, Petros Koumoutsakos
Modeling and simulation of complex fluid flows with dynamics that span multiple spatio-temporal scales is a fundamental challenge in many scientific and engineering domains. Full-s…
Generative Learning of the Solution of Parametric Partial Differential Equations Using Guided Diffusion Models and Virtual Observations
Han Gao, Sebastian Kaltenbach, Petros Koumoutsakos
We introduce a generative learning framework to model high-dimensional parametric systems using gradient guidance and virtual observations. We consider systems described by Partial…
Generative Learning for Forecasting the Dynamics of Complex Systems
Han Gao, Sebastian Kaltenbach, Petros Koumoutsakos
We introduce generative models for accelerating simulations of complex systems through learning and evolving their effective dynamics. In the proposed Generative Learning of Effect…
An adaptive model reduction method leveraging locally supported basis functions
Han Gao, Matthew J. Zahr
We propose a new method, the continuous Galerkin method with globally and locally supported basis functions (CG-GL), to address the parametric robustness issues of reduced-order mo…