no code implementations • 20 Dec 2023 • Shubhangi Ghosh, Luigi Gresele, Julius von Kügelgen, Michel Besserve, Bernhard Schölkopf
As typical in ICA, previous work focused on the case with an equal number of latent components and observed mixtures.
no code implementations • 13 Jul 2022 • Joanna Sliwa, Shubhangi Ghosh, Vincent Stimper, Luigi Gresele, Bernhard Schölkopf
One aim of representation learning is to recover the original latent code that generated the data, a task which requires additional information or inductive biases.
no code implementations • 14 Feb 2022 • Shubhangi Ghosh, Luigi Gresele, Julius von Kügelgen, Michel Besserve, Bernhard Schölkopf
Model identifiability is a desirable property in the context of unsupervised representation learning.