We tested whether Bayesian optimization could increase t 2 by selecting better hyperparameters. We optimized the search space in Table 2 using both single-objective and dual-objective optimization, with objectives based on the timescales, t 2/3 and the VAMP2 eq (2/3) scores, see Table for a list of optimization experiments. The optimization using dual objectives of t 2 with t 2 /t 3 (and the VAMP2 eq equivalent) was prompted by the observation that from the randomly sampled hyperparameter trial data set, there were many models with similar values of t 2 but with a wide range of timescale gaps t 2 /t 3 . A large timescale gap gives rise to models which are more accurate when truncated and coarse-grained into a two-state model.