4 papers
Reprogramming FairGANs with Variational Auto-Encoders: A New Transfer Learning Model
Beatrice Nobile, Gabriele Santin, Bruno Lepri +1
Fairness-aware GANs (FairGANs) exploit the mechanisms of Generative Adversarial Networks (GANs) to impose fairness on the generated data, freeing them from both disparate impact an…
Kernel methods for center manifold approximation and a data-based version of the Center Manifold Theorem
Bernard Haasdonk, Boumediene Hamzi, Gabriele Santin +1
For dynamical systems with a non hyperbolic equilibrium, it is possible to significantly simplify the study of stability by means of the center manifold theory. This theory allows…
Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario
Markus Köppel, Fabian Franzelin, Ilja Kröker +8
A variety of methods is available to quantify uncertainties arising with\-in the modeling of flow and transport in carbon dioxide storage, but there is a lack of thorough compariso…
Numerical modelling of a peripheral arterial stenosis using dimensionally reduced models and kernel methods
Tobias Köppl, Gabriele Santin, Bernard Haasdonk +1
In this work, we consider two kinds of model reduction techniques to simulate blood flow through the largest systemic arteries, where a stenosis is located in a peripheral artery i…