Jaewook Lee

Transfer Learning Architectures for Scalable Multi-Fidelity Bayesian Optimization

This work benchmarks eleven transfer-learning surrogates against four GP methods under an identical selection rule, fidelity budget, and model size, across nine tasks spanning synthetic functions to real chemistry and materials problems, where transfer-learning surrogates reach substantially better solutions using far less computation.