Coarse-grained models are known to suffer from the problem of high pressure unless explicitly trained for, which is also seen here. The models that include a pressure correction SP pc and T L pc outperform the other models (Fig. ). The only exception to this was the T L pc model for the PEG M1 mapping that shows an adverse effect of including the ML corrections. We note that pressure can be included in any forcematching framework as a constraint as done by Izvekov et al in the MSCG framework and can be applied to the DeePCG (ML/TL) models as well. Transfer learning with pressure corrected IBI is another approach to do so.