Addressing the Topological Defects of Disentanglement via Distributed Operators

Understand

A core challenge in Machine Learning is to learn to disentangle natural factors of variation in data (e.g.

• object shape vs.
• pose).
• A popular approach to disentanglement consists in learning to map each of these factors to distinct subspaces of a model's latent representation.