activity
20182021
collaborators

6 papers

cs.LG2021

Data-driven reduced order modeling of environmental hydrodynamics using deep autoencoders and neural ODEs

Sourav Dutta, Peter Rivera-Casillas, Orie M. Cecil +3

Model reduction for fluid flow simulation continues to be of great interest across a number of scientific and engineering fields. In a previous work [arXiv:2104.13962], we explored…

math.NA2021

Arbitrary-order intrinsic virtual element method for elliptic equations on surfaces

Elena Bachini, Gianmarco Manzini, Mario Putti

We develop a geometrically intrinsic formulation of the arbitrary-order Virtual Element Method (VEM) on polygonal cells for the numerical solution of elliptic surface partial diffe…

physics.soc-ph2020

Designing optimal networks for multi-commodity transport problem

Alessandro Lonardi, Enrico Facca, Mario Putti +1

Designing and optimizing different flows in networks is a relevant problem in many contexts. While a number of methods have been proposed in the physics and optimal transport liter…

physics.soc-ph2020

Network extraction by routing optimization

Diego Baptista, Daniela Leite, Enrico Facca +2

Routing optimization is a relevant problem in many contexts. Solving directly this type of optimization problem is often computationally unfeasible. Recent studies suggest that one…

math.NA2018

Physarum Dynamics and Optimal Transport for Basis Pursuit

Enrico Facca, Franco Cardin, Mario Putti

We study the connections between Physarum Dynamics and Dynamic Monge Kantorovich (DMK) Optimal Transport algorithms for the solution of Basis Pursuit problems. We show the equivale…

math.NA2018

Branching structures emerging from a continuous optimal transport model

Enrico Facca, Franco Cardin, Mario Putti

Recently a Dynamic-Monge-Kantorovich formulation of the PDE-based -optimal transport problem was presented. The model considers a diffusion equation enforcing the balance of t…