With multiple networks (different random seed at training) calculating the same total energy at each timestep, we could compute a spread (min/max-difference or standard error) of energies which indicates missing information in the training data.
Since no additional symmetry functions need to be calculated the performance will not be affected much.
With multiple networks (different random seed at training) calculating the same total energy at each timestep, we could compute a spread (min/max-difference or standard error) of energies which indicates missing information in the training data.
Since no additional symmetry functions need to be calculated the performance will not be affected much.