Table 1. Time required to compute excited state energies (10000 frames) for all bacteriochlorophylls (BChls) for TDDFT (PBE0/3-21G) and neural network (NN) predictions from correlation clustered Coulomb matrices. Reported times include neural network training (t_train) on 4000 frames with input (tinputCoul) and target feature (ttargetE) generation, excited state calculations/predictions (t_Calc) and the total time (t_tot). If trained neural networks are available, only Coulomb matrices need to be calculated for neural network predictions, reducing the required time to 48 h. Reported times correspond to training a total of 12 neural networks independently to obtain ensemble averaged excited state energies. All reported times refer to calculations on a single core of an Intel(R) Xeon(R) CPU (X5650 @ 2.67 GHz).

Method	Training [h]			Calculation [h]	Total [h]
	t input Coul	t target E	t train	t Calc	t tot
PBE0/3-21G	—	—	—	480000	480000
NNCorr	48	192000	9178	<0.1	201226