It is also instructive to benchmark our MatTEN model to historic models and previous state-of-the-art models to ensure that our model constitutes an advance in the field, especially for the domains where previous models were successful. For should be noted that one drawback of the SOAP descriptor is that its size scales with number of species in the dataset, N , as N (N -1), thus for our entire dataset the SOAP descriptor encoding has a size of 10980, and while this is not an issue for LRR, the dimensionality may be an issue for other methods especially as the descriptor size is far greater than the dataset size. It should also be noted that the LRR model can only handle scalar values, whereas the main benefit of the MatTEN model is in providing the full shift tensor.