Cargando…
Nonlinear independent component analysis for principled disentanglement in unsupervised deep learning
A central problem in unsupervised deep learning is how to find useful representations of high-dimensional data, sometimes called “disentanglement.” Most approaches are heuristic and lack a proper theoretical foundation. In linear representation learning, independent component analysis (ICA) has been...
| Autores principales: | , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2023
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10591132/ https://www.ncbi.nlm.nih.gov/pubmed/37876900 http://dx.doi.org/10.1016/j.patter.2023.100844 |