deep-kernel-learning

This paper introduces TTARO, an online deep-kernel Bayesian optimization framework that adapts circuit representations at test time using evaluated figure-of-merit labels. It improves sample efficiency for analog circuit topology search, reducing regret AUC by 15.2% over standard BO and 20.7% over fixed deep kernel learning.