2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 2 cited
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…
cs.LG2023
A few-shot graph Laplacian-based approach for improving the accuracy of low-fidelity data
Orazio Pinti, Assad A. Oberai
Low-fidelity data is typically inexpensive to generate but inaccurate. On the other hand, high-fidelity data is accurate but expensive to obtain. Multi-fidelity methods use a small…