The NTL9 dataset was provided by D. E. Shaw research . This dataset originally contained four trajectories with a total of 2.8 milliseconds simulation data. The trajectories were downsampled with a 2ns saving interval. The pairwise distances of all alpha carbon atoms were used as input features for tICA, AMUSEt, and AMUSET-TICA. In AMUSET-TICA, we adopted six Gaussian basis functions with 𝜎 = 0.5 following the same approach as alanine dipeptide, which yielded a rank-343 tensor-train structure. In AMUSEt, we adopted the same Gaussian basis set employed in the original presentation of AMUSEt 59 by using 𝑁 5 = 6 and 𝑟 9': = 200. The implied timescales were obtained from the transition probability matrix of a 1000-state MSM at 4000 ns lag time, and the 1000 states were generated with K-Centers clustering on three tICs with the tICA lag time of 1000 ns. The uncertainties of these implied timescales were computed using the same bootstrapping procedure as that used for alanine dipeptide system. We used these implied scales from the 1000-state MSM as the "ground truth" reference in the Results section.