3 papers
math.NA2026
Graph-Instructed Neural Networks for parametric problems with varying boundary conditions
Francesco Della Santa, Sandra Pieraccini, Maria Strazzullo
This work addresses the accurate and efficient simulation of physical phenomena governed by parametric Partial Differential Equations (PDEs) characterized by varying boundary condi…
cs.LG2024
Edge-Wise Graph-Instructed Neural Networks
Francesco Della Santa, Antonio Mastropietro, Sandra Pieraccini +1
The problem of multi-task regression over graph nodes has been recently approached through Graph-Instructed Neural Network (GINN), which is a promising architecture belonging to th…
math.NA2024
A Recipe for Learning Variably Scaled Kernels via Discontinuous Neural Networks
Gianluca Audone, Francesco Della Santa, Emma Perracchione +1
The efficacy of interpolating via Variably Scaled Kernels (VSKs) is known to be dependent on the definition of a proper scaling function, but no numerical recipes to construct it a…