Preprints

Published

[11] Federico Pichi, Francesco Ballarin, Gianluigi Rozza, Jan Hesthaven. An Artificial Neural Network Approach to Bifurcating Phenomena in Computational Fluid Dynamics. Computers & Fluids, 2023

[8] F. Pichi, F. Ballarin, G. Rozza, J. Hesthaven. Artificial neural network for bifurcating phenomena modelled by nonlinear parametrized PDEs. PAMM, 2021

[7] M. Pintore, F. Pichi, M. Hess, G. Rozza, C. Canuto. Efficient computation of bifurcation diagrams with a deflated approach to reduced basis spectral element method. Advances in Computational Mathematics, 2020

[6] F. Pichi, A. Quaini, G. Rozza. A Reduced Order Modeling Technique to Study Bifurcating Phenomena: Application to the Gross-Pitaevskii Equation. SIAM Journal on Scientific Computing, 2020

[5] F. Pichi, G. Rozza. Reduced basis approaches for parametrized bifurcation problems held by non-linear Von Karman equations. Journal of Scientific Computing, 2019

Proceedings