Federico Pichi
Orcid: 0000-0002-1163-3386
According to our database1,
Federico Pichi authored at least 27 papers
between 2019 and 2026.
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Bibliography
2026
J. Sci. Comput., July, 2026
Stochastic bifurcation analysis via polynomial chaos: consistency and convergence of branch-approximating solutions.
CoRR, May, 2026
Integrating Artificial Intelligence, Physics, and Internet of Things: A Framework for Cultural Heritage Conservation.
CoRR, April, 2026
A Multi-Fidelity Parametric Framework for Reduced-Order Modeling using Optimal Transport-based Interpolation: Applications to Diffused-Interface Two-Phase Flows.
CoRR, March, 2026
CoRR, February, 2026
Latent Dynamics Graph Convolutional Networks for model order reduction of parameterized time-dependent PDEs.
CoRR, January, 2026
2025
ROM for Viscous, Incompressible Flow in Polygons - exponential <i>n</i>-width bounds and convergence rate.
CoRR, December, 2025
Time Extrapolation with Graph Convolutional Autoencoder and Tensor Train Decomposition.
CoRR, November, 2025
Convergence and Sketching-Based Efficient Computation of Neural Tangent Kernel Weights in Physics-Based Loss.
CoRR, November, 2025
CoRR, February, 2025
Nonlinear reduction strategies for data compression: a comprehensive comparison from diffusion to advection problems.
CoRR, January, 2025
Optimal Transport-Inspired Deep Learning Framework for Slow-Decaying Kolmogorov \({n}\)-Width Problems: Exploiting Sinkhorn Loss and Wasserstein Kernel.
SIAM J. Sci. Comput., 2025
SIAM J. Sci. Comput., 2025
Optimal transport-based displacement interpolation with data augmentation for reduced order modeling of nonlinear dynamical systems.
J. Comput. Phys., 2025
Deflation-based certified greedy algorithm and adaptivity for bifurcating nonlinear PDEs.
Commun. Nonlinear Sci. Numer. Simul., 2025
Projection-based reduced order modelling for unsteady parametrized optimal control problems in 3D cardiovascular flows.
Comput. Methods Programs Biomed., 2025
2024
A graph convolutional autoencoder approach to model order reduction for parametrized PDEs.
J. Comput. Phys., March, 2024
GFN: A graph feedforward network for resolution-invariant reduced operator learning in multifidelity applications.
CoRR, 2024
2023
Optimal Transport-inspired Deep Learning Framework for Slow-Decaying Problems: Exploiting Sinkhorn Loss and Wasserstein Kernel.
CoRR, 2023
2021
Model order reduction for bifurcating phenomena in Fluid-Structure Interaction problems.
CoRR, 2021
An artificial neural network approach to bifurcating phenomena in computational fluid dynamics.
CoRR, 2021
Efficient computation of bifurcation diagrams with a deflated approach to reduced basis spectral element method.
Adv. Comput. Math., 2021
2020
A Reduced Order Modeling Technique to Study Bifurcating Phenomena: Application to the Gross-Pitaevskii Equation.
SIAM J. Sci. Comput., 2020
Driving bifurcating parametrized nonlinear PDEs by optimal control strategies: application to Navier-Stokes equations with model order reduction.
CoRR, 2020
2019
Reduced Basis Approaches for Parametrized Bifurcation Problems held by Non-linear Von Kármán Equations.
J. Sci. Comput., 2019
A Reduced Order technique to study bifurcating phenomena: application to the Gross-Pitaevskii equation.
CoRR, 2019