1 citations · 1 across the 3 of their papers we have counts for
4 papers
Operator Learning with Gaussian Processes
Carlos Mora, Amin Yousefpour, Shirin Hosseinmardi +2
Operator learning focuses on approximating mappings between infinite-dimensional spaces of functions, such as $u: Ω_u\right…
Unveiling Processing--Property Relationships in Laser Powder Bed Fusion: The Synergy of Machine Learning and High-throughput Experiments
Mahsa Amiri, Zahra Zanjani Foumani, Penghui Cao +2
Achieving desired mechanical properties in additive manufacturing requires many experiments and a well-defined design framework becomes crucial in reducing trials and conserving re…
Data Fusion with Latent Map Gaussian Processes
Nicholas Oune, Jonathan Tammer Eweis-Labolle, Ramin Bostanabad
Multi-fidelity modeling and calibration are data fusion tasks that ubiquitously arise in engineering design. In this paper, we introduce a novel approach based on latent-map Gaussi…
Latent Map Gaussian Processes for Mixed Variable Metamodeling
Nicholas Oune, Ramin Bostanabad
Gaussian processes (GPs) are ubiquitously used in sciences and engineering as metamodels. Standard GPs, however, can only handle numerical or quantitative variables. In this paper,…