collaborators

16 papers

math.NA2026

A Dynamical Approximation Scheme on the Stiefel manifold for Wasserstein Gradient Flows

Isabella Carla Gonnella, Olga Mula, Federico Pichi +1

We propose a meshless Lagrangian dynamical method for approximating Wasserstein gradient flows (WGFs). The evolving measure is represented as the pushforward of the initial measure…

math.NA2026

Bifurcation curve detection with deflation for multiparametric PDEs

Nitin Kumar, Federico Pichi, Gianluigi Rozza

This work presents a comprehensive framework for capturing bifurcating phenomena and detecting bifurcation curves in nonlinear multiparametric partial differential equations, where…

math.NA2026

Stochastic bifurcation analysis via polynomial chaos: consistency and convergence of branch-approximating solutions

Giacomo Venier, Isabella Carla Gonnella, Federico Pichi +1

Parameter-dependent dynamical systems that exhibit bifurcations pose significant computational challenges, as traditional continuation methods require repeated, costly simulations…

math.NA2026

A Multi-Fidelity Parametric Framework for Reduced-Order Modeling using Optimal Transport-based Interpolation: Applications to Diffused-Interface Two-Phase Flows

Moaad Khamlich, Niccolò Tonicello, Federico Pichi +1

This work introduces a data-driven, non-intrusive reduced-order modeling (ROM) framework that leverages Optimal Transport (OT) for multi-fidelity and parametric problems in two-pha…

math.NA2026

Nonlinear reduction strategies for data compression: a comprehensive comparison from diffusion to advection problems

Isabella Carla Gonnella, Federico Pichi, Gianluigi Rozza

This work presents an overview of several nonlinear reduction strategies for data compression from various research fields, and a comparison of their performance when applied to pr…

math.NA2026

A stochastic perturbation approach to nonlinear bifurcating problems

Isabella Carla Gonnella, Moaad Khamlich, Federico Pichi +1

Incorporating probabilistic terms in mathematical models is crucial for capturing and quantifying uncertainties in real-world systems, especially when the solution is not unique or…