: You can share compact "latent representations" instead of entire raw trajectories, making collaboration easier.

: It doesn't need complex physics rules during the compression phase, making it faster and more flexible.

: The decoder reconstructs the atomic positions with high geometric accuracy.

: Only the compressed latent data and the trained model weights need to be stored.

: Despite high compression, it preserves ensemble-level features like RMSD fluctuations and radius of gyration.