14 citations · 36 across the 10 of their papers we have counts for
3 papers · 1 filter
Accurate and Uncertainty-Aware Multi-Task Prediction of HEA Properties Using Prior-Guided Deep Gaussian Processes
Sk Md Ahnaf Akif Alvi, Mrinalini Mulukutla, Nicolas Flores +6
Surrogate modeling techniques have become indispensable in accelerating the discovery and optimization of high-entropy alloys(HEAs), especially when integrating computational predi…
Towards Autonomous Experimentation: Bayesian Optimization over Problem Formulation Space for Accelerated Alloy Development
Danial Khatamsaz, Joseph Wagner, Brent Vela +2
Accelerated discovery in materials science demands autonomous systems capable of dynamically formulating and solving design problems. In this work, we introduce a novel framework t…
Microstructure-Aware Bayesian Materials Design
Danial Khatamsaz, Vahid Attari, Raymundo Arroyave
In this study, we propose a novel microstructure-sensitive Bayesian optimization (BO) framework designed to enhance the efficiency of materials discovery by explicitly incorporatin…