A detailed overview of the training set for MLS2 is given in Sec. S8 in the SI. For the architecture of the MLS2's NN, we used four hidden layers with 64 neurons each. The layers were again connected via hyperbolic tangent functions, except the output layer, which was linked via a sigmoid logistic function. Each individual weight contribution was scaled by a factor of ten. The total loss function contains total and interaction correlation energy errors, as detailed in Sec. S4 in the SI. Here, the learning rate follows also an exponential decay over 1000 epochs.