V. Krokos

A Graph-based probabilistic geometric deep learning framework with online physics-based corrections to predict the criticality of defects in porous materials

P. Kerfriden, S. Bordas, V. Krokos, 2022, ArXiv.

A Bayesian multiscale CNN framework to predict local stress fields in structures with microscale features

Philippe Young, Pierre Kerfriden, Stéphane P. A. Bordas, 2020, Computational Mechanics.

Optimization of Patterned Surfaces for Improved Superhydrophobicity through Cost-Effective Large-Scale Computations.

G Kokkoris, A. N. Spyropoulos, V Krokos, 2019, Langmuir : the ACS journal of surfaces and colloids.

Bayesian Convolutional Neural Networks as probabilistic surrogates for the fast prediction of stress fields in structures with microscale features pdf

Pierre Kerfriden, V. B. Xuan, Philippe Young, 2020, ArXiv.