The number of Gaussian basis functions 𝑁 5 is an important hyperparameter for the AMUSET-TICA method, as substantiated in this subsection by the performance of the AMUSET-TICA when varying this hyperparameter. Upon comparison of the performance for alanine dipeptide of two AMUSET-TICA models (i.e., 𝑁 5 = 6 and 𝑁 5 = 2, corresponding to rank-343 and rank-27 models, Figure ), the CVs show that the projections of MD conformations onto the top three tICs all display two-peak distributions (Figure ). This result supports the use of two Gaussian functions for each tIC, resulting in a total of 6 Gaussian basis functions for 3 tICs (𝑁 5 = 6). Furthermore, the CVs show that the choice of 𝜎 = 1.3 can ensure substantial overlap between the Gaussian basis functions (Figure ). When evaluating whether the Gaussian basis functions with 𝜎 = 1.3 adequately cover the phase space of the alanine dipeptide, projection of the functions onto tIC1 and tIC2 indicates that the Gaussian basis functions effectively span the sampled regions (Figure ). In contrast, using 𝜎 = 0.05 resulted in projections that failed to cover the sampled phase space (Figure ). The resulting AMUSET-TICA model (red lines in Figure ) has the rank of (6 + 1) N = 343. When further assessing the impact of number of Gaussian basis functions on the performance of our method, a control AMUSET-TICA model containing only two Gaussian basis functions, with means chosen to match the tIC1 distribution and 𝜎 = 2, has a rank of 27 (purple lines in Figure ).