Anna Ivagnes

According to our database, Anna Ivagnes authored at least 15 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Efficient and Accurate Surrogate Modeling of Turbulent Flows via Space-Dependent Aggregation and Reduced Order Models.

Piero Zappi, Anna Ivagnes, Niccolò Tonicello, Gianluigi Rozza

CoRR, March, 2026

Reinforcement Learning-Based Filters for Convection-Dominated Flows: Reference-Free and Reference-Guided Training.

Anna Ivagnes, Maria Strazzullo, Gianluigi Rozza

CoRR, March, 2026

StabOp: A Data-Driven Stabilization Operator for Reduced Order Modeling.

Ping-Hsuan Tsai, Anna Ivagnes, Annalisa Quaini, Traian Iliescu, Gianluigi Rozza

CoRR, February, 2026

2025

A new data-driven energy-stable Evolve-Filter-Relax model for turbulent flow simulation.

Anna Ivagnes, Toby van Gastelen, Syver Døving Agdestein, Benjamin Sanderse, Giovanni Stabile, Gianluigi Rozza

CoRR, July, 2025

Machine Learning-based quadratic closures for non-intrusive Reduced Order Models.

Gabriele Codega, Anna Ivagnes, Nicola Demo, Gianluigi Rozza

CoRR, June, 2025

Data-driven Closure Strategies for Parametrized Reduced Order Models via Deep Operator Networks.

Anna Ivagnes, Giovanni Stabile, Gianluigi Rozza

CoRR, May, 2025

Data-driven Optimization for the Evolve-Filter-Relax regularization of convection-dominated flows.

Anna Ivagnes, Maria Strazzullo, Michele Girfoglio, Traian Iliescu, Gianluigi Rozza

CoRR, January, 2025

2024

Parametric Intrusive Reduced Order Models enhanced with Machine Learning Correction Terms.

Anna Ivagnes, Giovanni Stabile, Gianluigi Rozza

CoRR, 2024

Enhancing non-intrusive Reduced Order Models with space-dependent aggregation methods.

Anna Ivagnes, Niccolò Tonicello, Paola Cinnella, Gianluigi Rozza

CoRR, 2024

2023

Hybrid data-driven closure strategies for reduced order modeling.

Anna Ivagnes, Giovanni Stabile, Andrea Mola, Traian Iliescu, Gianluigi Rozza

Appl. Math. Comput., July, 2023

PINA: Physics-Informed Neural networks for Advanced modeling.

Dario Coscia, Anna Ivagnes, Nicola Demo, Gianluigi Rozza

Dataset, July, 2023

Towards a Machine Learning Pipeline in Reduced Order Modelling for Inverse Problems: Neural Networks for Boundary Parametrization, Dimensionality Reduction and Solution Manifold Approximation.

Anna Ivagnes, Nicola Demo, Gianluigi Rozza

J. Sci. Comput., April, 2023

Pressure data-driven variational multiscale reduced order models.

Anna Ivagnes, Giovanni Stabile, Andrea Mola, Traian Iliescu, Gianluigi Rozza

J. Comput. Phys., March, 2023

Physics-Informed Neural networks for Advanced modeling.

Dario Coscia, Anna Ivagnes, Nicola Demo, Gianluigi Rozza

J. Open Source Softw., 2023

A shape optimization pipeline for marine propellers by means of reduced order modeling techniques.

Anna Ivagnes, Nicola Demo, Gianluigi Rozza

CoRR, 2023