For NTL9, AMUSET-TICA, AMUSEt, and tICA all predict the three slowest ITS in reasonable agreement with the ground truth, provided the lag time is sufficiently long (Figure (a)). However, both AMUSEt and tICA require significantly longer lag times (400 ns for CV1, 800 ns for CV2, and 500 ns for CV3) compared to AMUSET-TICA, which achieves accurate predictions of ITS at much shorter lag times (100 ns for CV1, 400 ns for CV2, and 100 ns for CV3). This demonstrates the superior performance of AMUSET-TICA. Note the same ranking of pairwise 𝐶 'QRS' distances of NTL9 was used here for the AMUSEt model as in the previous study , in which the ordering was optimized based on physical intuition; however, AMUSEt lacks a systematic and automated method for effectively ranking input features, which limits its performance. AMUSET-TICA overcomes this challenge by utilizing the top tICs as the basis for expansion into Gaussian functions.