Compared to hard condensed matter, soft matter lags behind in terms of ML integration, in large part due to the need to address the associated conformational flexibility. One outstanding challenge lies at the level of system representation, i.e., how to encode the fluctuating system configuration for input to an ML model. Atomic representations developed for electronic properties have focused on single configurations (e.g., ). Here instead, observables are averaged over a typically very broad Boltzmann distribution of configurations. Much less work has been proposed in the context of ensemble-averaged ML representations, though ideas have been proposed , .