cond-mat.mtrl-sci · 2026-07-09 · No. 48
Materials Science, 2026-07-09.
1 new papers in cond-mat.mtrl-sci. Titles, authors,
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01 — The papers
1 entries-
01
Bayesian Optimization of Genetic Algorithm Hyperparameters in a Multi-Fidelity Framework for Efficient Lattice Material Design
Sergei Zorkaltsev, Maciej Haranczyk, Christina Schenk
cond-mat.mtrl-sci · cond-mat.dis-nn · cs.AI · cs.LG · math.OC
This study presents a multi-fidelity framework for the systematic optimization of genetic algorithm (GA) hyperparameters. The framework integrates three fidelity levels: high-fidelity Fast Fourier Transform (FFT) homogenization for validation, a medium-fidelity 3D convolutional neural network surrogate for rapid property evaluation, and a low-fidelity Gaussian process (GP) surrogate within a Bayesian optimization (BO) framework to guide the...
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