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David Montes de Oca Zapiain
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1
MATSE—multi-fidelity augmented time-series emulation: galvanic corrosion applications
by
Aditya Venkatraman
,
Ryan M Katona
,
David Montes de Oca Zapiain
Published in
Machine Learning: Science and Technology
(2025-01-01)
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2
Accelerating charge estimation in molecular dynamics simulations using physics-informed neural networks: corrosion applications
by
Aditya Venkatraman
,
Mark A. Wilson
,
David Montes de Oca Zapiain
Published in
npj Computational Materials
(2025-02-01)
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3
Neural network ensembles and uncertainty estimation for predictions of inelastic mechanical deformation using a finite element method-neural network approach
by
Guy L. Bergel
,
David Montes de Oca Zapiain
,
Vicente Romero
Published in
Data-Centric Engineering
(2023-01-01)
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4
Texture-sensitive prediction of micro-spring performance using Gaussian process models calibrated to finite element simulations
by
Aditya Venkatraman
,
David Montes de Oca Zapiain
,
Hojun Lim
,
Surya R. Kalidindi
Published in
Materials & Design
(2021-01-01)
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5
Investigating the orientation dependence of local fields around spherical defects using crystal plasticity simulations
by
Nicole K. Aragon
,
Aashique A. Rezwan
,
David Montes de Oca Zapiain
,
Hojun Lim
Published in
Journal of Materials Research and Technology
(2024-11-01)
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6
An active learning framework for the rapid assessment of galvanic corrosion
by
Aditya Venkatraman
,
Ryan Michael Katona
,
Demitri Maestas
,
Matthew Roop
,
Philip Noell
,
David Montes de Oca Zapiain
Published in
npj Materials Degradation
(2024-05-01)
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7
Training data selection for accuracy and transferability of interatomic potentials
by
David Montes de Oca Zapiain
,
Mitchell A. Wood
,
Nicholas Lubbers
,
Carlos Z. Pereyra
,
Aidan P. Thompson
,
Danny Perez
Published in
npj Computational Materials
(2022-09-01)
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