2019/06/24 by X. Dong, Xingrong Dong, L. Zhou +3 · 1 citation
Computer Science · Physics and Astronomy · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Relativity and Gravitational Theory #cs.AI #cs.LG
paper · pdf · doi:10.48550/arxiv.1906.10545
5 pages, 2 figures, draft version
arxiv created 2019/06/24 · openalex publication_date 2019/06/24 · arxiv updated 2019/06/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Achieving disentangled representations of information is one of the key goals of deep network based machine learning system. Recently there are more discussions on this issue. In this paper, by comparing the geometric structure of disentangled representation and the geometry of the evolution of mixed states in quantum mechanics, we give a fibre bundle based geometric picture of disentangled representation which can be regarded as a kind of gauge theory. From this perspective we can build a connection between the disentangled representations and the twins paradox in relativity. This can help to clarify some problems about disentangled representation.