Abstract: Computer models for bodies based on vertex-based models are enriched by adding nonlinear soft-tissue dynamics to the traditional piece-wise rigid meshes. A neural network is provided for real-time nonlinear soft-tissue regression to enrich skinned 3D animated sequences. The neural network is trained to predict 3D offsets from joint angle velocities and accelerations, as well as earlier dynamic components. The per-vertex rigidity is computed and leveraged to obtain a better-behaved minimization problem. A novel autoencoder is also provided for dimensionality reduction of the 3D vertex displacements that represent nonlinear soft-tissue dynamics in 3D mesh sequences.