2 papers
cs.LG2025
Graph Laplacian-based Bayesian Multi-fidelity Modeling
Orazio Pinti, Jeremy M. Budd, Franca Hoffmann +1
We present a novel probabilistic approach for generating multi-fidelity data while accounting for errors inherent in both low- and high-fidelity data. In this approach a graph Lapl…
math.NA2025
An optimal Petrov-Galerkin framework for operator networks
Philip Charles, Deep Ray, Yue Yu +7
The optimal Petrov-Galerkin formulation to solve partial differential equations (PDEs) recovers the best approximation in a specified finite-dimensional (trial) space with respect…