5 papers
Bayesian optimization for stable properties amid processing fluctuations in sputter deposition
Ankit Shrivastava, Matias Kalaswad, Joyce O. Custer +2
We introduce a Bayesian optimization approach to guide the sputter deposition of molybdenum thin films, aiming to achieve desired residual stress and sheet resistance while minimiz…
Bayesian Nonlocal Operator Regression (BNOR): A Data-Driven Learning Framework of Nonlocal Models with Uncertainty Quantification
Yiming Fan, Marta D'Elia, Yue Yu +2
We consider the problem of modeling heterogeneous materials where micro-scale dynamics and interactions affect global behavior. In the presence of heterogeneities in material micro…
Scalable approximation of Green's function for estimation of anharmonic energy corrections
Prashant Rai, Khachik Sargsyan, Habib Najm +1
A method based on separated integration to estimate anharmonic corrections to energy and vibration of molecules in a second-order diagrammatic vibrational many-body Green's functio…
Sparse Low Rank Approximation of Potential Energy Surfaces with Applications in Estimation of Anharmonic Zero Point Energies and Frequencies
Prashant Rai, Khachik Sargsyan, Habib Najm +1
We propose a method that exploits sparse representation of potential energy surfaces (PES) on a polynomial basis set selected by compressed sensing. The method is useful for studie…
Entropy-based closure for probabilistic learning on manifolds
C. Soizea, R. Ghanem, C. Safta +7
In a recent paper, the authors proposed a general methodology for probabilistic learning on manifolds. The method was used to generate numerical samples that are statistically cons…