Improving Disentangled Representation Learning by Combining Penalty-based and Multi-Stage Modeling

A novel multi-stage modeling approach that first learns disentangled factors using a penalty-based method and then improves the reconstruction quality by learning additional correlated latent variables, while maintaining the conditioning on the disentangled factors.