collaborators

6 papers

math.PR2026

Nonlinear parabolic characterizations of stochastic completeness at infinity on weighted graphs

Davide Bianchi, Bobo Hua, Alberto G. Setti +1

We prove a nonlinear parabolic characterization of stochastic completeness at infinity for weighted graphs. For the filtration equation \[ (\partial_t + ΔΦ)u =0 \] where is the…

math.AP2026

The generalized porous medium equation on graphs: well-posedness, extinction, and mass conservation

Davide Bianchi, Bobo Hua, Alberto G. Setti +1

We study the Cauchy problem for the generalized porous medium equation on infinite weighted graphs. For a general nonlinearity, we establish Dirichlet comparison and weak maximum p…

math.FA2026

On the accretivity and m-accretivity of Laplacians and porous medium-type operators on graphs

Davide Bianchi, Matthias Keller, Alberto G. Setti +2

We study the accretivity and m-accretivity of Laplacian and porous medium-type operators on weighted graphs. In particular, we give several conditions that imply these properties f…

math.AP2026

Semilinear Diffusion Equations on Infinite Graphs: The Dissipative and Lipschitz Cases

Elvise Berchio, Davide Bianchi, Alberto G. Setti +1

We study a class of semilinear diffusion equations on infinite, connected, weighted graphs, focusing on two types of nonlinearities: monotone decreasing and Lipschitz continuous. U…

math.OC2025

Variable Projected Augmented Lagrangian Methods for Generalized Lasso Problems

Stefano Aleotti, Davide Bianchi, Florian Bossmann +2

We introduce variable projected augmented Lagrangian (VPAL) methods for solving generalized nonlinear Lasso problems with improved speed and accuracy. By eliminating the nonsmooth…

math.NA2025

Improved impedance inversion by the iterated graph Laplacian

Davide Bianchi, Florian Bossmann, Wenlong Wang +1

We introduce a data-adaptive inversion method that integrates classical or deep learning-based approaches with iterative graph Laplacian regularization, specifically targeting acou…