4 papers
PYTHIA, a transferable machine learning framework for simultaneous defect and adsorption site optimization
Ioannis Kouroudis, Zhaosu Gu, Poonam +2
Machine learning has permeated material optimization, providing high value. Nevertheless, its re- liance on a high number of samples limits its applicability to relatively explored…
Accelerated surrogate dynamics for dynamical, stochastic system evolution
Marco Jochum, Ioannis Kouroudis, Gohar Ali Siddiqui +3
Dynamic simulations are an entrenched way of gaining insight into the evolution of system dynamics. Their computational cost however is often prohibitively high, especially in case…
Probabilistic Deep Learning Framework for Phase Transformation Forecasting aided by In Situ High temperature Microscopy
Ioannis Kouroudis, Niki Balestrieri, Stefan Rotzsche +3
The mechanical performance of structural materials is governed by their microstructure, which is itself set by the thermal history imposed during processing. Predicting how that mi…
AUGUR, A flexible and efficient optimization algorithm for identification of optimal adsorption sites
Ioannis Kouroudis, Poonam, Neel Misciaci +4
In this paper, we propose a novel flexible optimization pipeline for determining the optimal adsorption sites, named AUGUR (Aware of Uncertainty Graph Unit Regression). Our model c…